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Patrick Groenen

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Author Profile
    1. Patrick Groenen in Wikipedia (English)

Working papers

  1. Richard Karlsson Linnér & Pietro Biroli & Edward Kong & S. Fleur W. Meddens & Robee Wedow & Mark Alan Fontana & Maël Lebreton & Abdel Abdellaoui & Anke R. Hammerschlag & Michel G. Nivard & Aysu Okba, 2018. "Genome-wide association analyses of risk tolerance and risky behaviors in over one million individuals identify hundreds of loci and shared genetic influences," Working Papers 2018-087, Human Capital and Economic Opportunity Working Group.

    Cited by:

    1. Vikesh Amin & Jere R. Behrman & Jason M. Fletcher & Carlos A. Flores & Alfonso Flores-Lagunes & Hans-Peter Kohler, 2020. "Genetic Risks, Adolescent Health and Schooling Attainment," PIER Working Paper Archive 20-024, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    2. Zhaonan Qu & Ruoxuan Xiong & Jizhou Liu & Guido Imbens, 2021. "Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference," Papers 2107.12420, arXiv.org, revised Jun 2024.
    3. Chowdhury, Shyamal & Sutter, Matthias & Zimmermann, Klaus F., 2020. "Economic preferences across generations and family clusters: A large-scale experiment," GLO Discussion Paper Series 592, Global Labor Organization (GLO).
    4. Nicos Nicolaou & Scott Shane, 2019. "Common genetic effects on risk-taking preferences and choices," Journal of Risk and Uncertainty, Springer, vol. 59(3), pages 261-279, December.
    5. Silvia Angerer & E. Glenn Dutcher & Daniela Glätzle-Rützler & Philipp Lergetporer & Matthias Sutter, 2021. "The Formation of Risk Preferences Through Small-Scale Events," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2021_16, Max Planck Institute for Research on Collective Goods.
    6. Giorgia Menta & Anthony Lepinteur & Andrew E Clark & Simone Ghislandi & Conchita d'Ambrosio, 2021. "Maternal depression and child human capital: A genetic instrumental-variable approach," PSE Working Papers halshs-03157270, HAL.
    7. Atticus Bolyard & Peter Savelyev, 2021. "Understanding the Educational Attainment Polygenic Index and its Interactions with SES in Determining Health in Young Adulthood," Working Papers 2021-026, Human Capital and Economic Opportunity Working Group.
    8. Francesconi, Marco & Barban, Nicola & De Cao, Elisabetta, 2021. "Gene-Environment Effects on Female Fertility," CEPR Discussion Papers 16603, C.E.P.R. Discussion Papers.
    9. John A. List & Ragan Petrie & Anya Samek, 2023. "How Experiments with Children Inform Economics," Journal of Economic Literature, American Economic Association, vol. 61(2), pages 504-564, June.
    10. Jason M. Fletcher & Qiongshi Lu, 2021. "Health policy and genetic endowments: Understanding sources of response to Minimum Legal Drinking Age laws," Health Economics, John Wiley & Sons, Ltd., vol. 30(1), pages 194-203, January.
    11. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    12. Andrea G Allegrini & Ville Karhunen & Jonathan R I Coleman & Saskia Selzam & Kaili Rimfeld & Sophie von Stumm & Jean-Baptiste Pingault & Robert Plomin, 2020. "Multivariable G-E interplay in the prediction of educational achievement," PLOS Genetics, Public Library of Science, vol. 16(11), pages 1-20, November.

  2. David A. Bennett & Klaus Berger & Lars Bertram & Hans Bisgaard & Dorret I. Boomsma & Ingrid B. Borecki & Ute Bültmann & Christopher F. Chabris & Francesco Cucca & Daniele Cusi & Ian J. Deary & George , 2016. "Genome-wide association study identifies 74 loci associated with educational attainment," Post-Print hal-02017372, HAL.

    Cited by:

    1. Ronald de Vlaming & Aysu Okbay & Cornelius A Rietveld & Magnus Johannesson & Patrik K E Magnusson & André G Uitterlinden & Frank J A van Rooij & Albert Hofman & Patrick J F Groenen & A Roy Thurik & Ph, 2017. "Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies," PLOS Genetics, Public Library of Science, vol. 13(1), pages 1-23, January.
    2. Pietro Biroli & Titus Galama & Stephanie von Hinke & Hans van Kippersluis & Kevin Thom, 2022. "Economics and Econometrics of Gene-Environment Interplay," Bristol Economics Discussion Papers 22/759, School of Economics, University of Bristol, UK.
    3. Shelly Lundberg & Aloysius Siow, 2017. "Canadian contributions to family economics," Canadian Journal of Economics, Canadian Economics Association, vol. 50(5), pages 1304-1323, December.
    4. Viinikainen, Jutta & Bryson, Alex & Böckerman, Petri & Elovainio, Marko & Hutri-Kähönen, Nina & Juonala, Markus & Lehtimäki, Terho & Pahkala, Katja & Rovio, Suvi & Pulkki-Råback, Laura & Raitakari, Ol, 2020. "Do childhood infections affect labour market outcomes in adulthood and, if so, how?," Economics & Human Biology, Elsevier, vol. 37(C).
    5. A. Roy Thurik & David B. Audretsch & Jörn H. Block & Andrew Burke & Martin A. Carree & Marcus Dejardin & Cornelius A. Rietveld & Mark Sanders & Ute Stephan & Johan Wiklund, 2024. "The impact of entrepreneurship research on other academic fields," Small Business Economics, Springer, vol. 62(2), pages 727-751, February.
    6. Hyeokmoon Kweon & Casper A. P. Burik & Yuchen Ning & Rafael Ahlskog & Charley Xia & Erik Abner & Yanchun Bao & Laxmi Bhatta & Tariq O. Faquih & Maud Feijter & Paul Fisher & Andrea Gelemanović & Alexan, 2025. "Associations between common genetic variants and income provide insights about the socio-economic health gradient," Nature Human Behaviour, Nature, vol. 9(4), pages 794-805, April.
    7. Akimova, Evelina T. & Wolfram, Tobias & Ding, Xuejie & Tropf, Felix C. & Mills, Melinda C., 2025. "Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 9(Febuary), pages 391-405.
    8. Lauren L. Schmitz & Dalton Conley, 2016. "The Effect of Vietnam-Era Conscription and Genetic Potential for Educational Attainment on Schooling Outcomes," NBER Working Papers 22393, National Bureau of Economic Research, Inc.
    9. Stephanie von Hinke & Emil Sorensen, 2022. "The Long-Term Effects of Early-Life Pollution Exposure: Evidence from the London Smog," Bristol Economics Discussion Papers 22/757, School of Economics, University of Bristol, UK.
    10. Hilger, Kirsten & Spinath, Frank M. & Troche, Stefan & Schubert, Anna-Lena, 2022. "The biological basis of intelligence: Benchmark findings," Intelligence, Elsevier, vol. 93(C).
    11. Victor Ronda & Esben Agerbo & Dorthe Bleses & Preben Bo Mortensen & Anders Børglum & Ole Mors & Michael Rosholm & David M. Hougaard & Merete Nordentoft & Thomas Werge, 2022. "Family disadvantage, gender, and the returns to genetic human capital," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(2), pages 550-578, April.
    12. Nicholas W. Papageorge & Kevin Thom, 2018. "Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study," Working Papers 2018-076, Human Capital and Economic Opportunity Working Group.
    13. Brooke M Huibregtse & Breanne L Newell-Stamper & Benjamin W Domingue & Jason D Boardman & Anna Zajacova, 2021. "Genes Related to Education Predict Frailty Among Older Adults in the United States [Genetic analysis of social-class mobility in five longitudinal studies]," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 76(1), pages 173-183.
    14. Mitchell, Brittany L. & Hansell, Narelle K. & McAloney, Kerrie & Martin, Nicholas G. & Wright, Margaret J. & Renteria, Miguel E. & Grasby, Katrina L., 2022. "Polygenic influences associated with adolescent cognitive skills," Intelligence, Elsevier, vol. 94(C).
    15. Lucía de Hoyos & Maria T. Barendse & Fenja Schlag & Marjolein M. J. van Donkelaar & Ellen Verhoef & Chin Yang Shapland & Alexander Klassmann & Jan Buitelaar & Brad Verhulst & Simon E. Fisher & Dheeraj, 2024. "Structural models of genome-wide covariance identify multiple common dimensions in autism," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    16. Morten Dybdahl Krebs & Gonçalo Espregueira Themudo & Michael Eriksen Benros & Ole Mors & Anders D. Børglum & David Hougaard & Preben Bo Mortensen & Merete Nordentoft & Michael J. Gandal & Chun Chieh F, 2021. "Associations between patterns in comorbid diagnostic trajectories of individuals with schizophrenia and etiological factors," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    17. Cawley, John & Han, Euna & Kim, Jiyoon & Norton, Edward C., 2023. "Genetic nurture in educational attainment," Economics & Human Biology, Elsevier, vol. 49(C).
    18. Edwards, Tobias & Dawes, Christopher T. & Willoughby, Emily A. & McGue, Matt & Lee, James J., 2025. "More than g: Verbal and performance IQ as predictors of socio-political attitudes," Intelligence, Elsevier, vol. 108(C).
    19. Chris Bidner & John Knowles, 2018. "Matching for Social Mobility with Unobserved Heritable Characteristics," Discussion Papers dp18-05, Department of Economics, Simon Fraser University.
    20. Nieuwenhuis, Jaap & Kleinepier, Tom & van Ham, Maarten, 2019. "Neighbourhood and School Poverty Simultaneously Predicting Educational Achievement, Taking into Account Timing and Duration of Exposure," IZA Discussion Papers 12396, Institute of Labor Economics (IZA).
    21. Silvia H. Barcellos & Leandro Carvalho & Patrick Turley, 2021. "The Effect of Education on the Relationship between Genetics, Early-Life Disadvantages, and Later-Life SES," NBER Working Papers 28750, National Bureau of Economic Research, Inc.
    22. Tzu-Ting Chen & Jaeyoung Kim & Max Lam & Yi-Fang Chuang & Yen-Ling Chiu & Shu-Chin Lin & Sang-Hyuk Jung & Beomsu Kim & Soyeon Kim & Chamlee Cho & Injeong Shim & Sanghyeon Park & Yeeun Ahn & Aysu Okbay, 2024. "Shared genetic architectures of educational attainment in East Asian and European populations," Nature Human Behaviour, Nature, vol. 8(3), pages 562-575, March.
    23. Mathias Seviiri & Matthew H. Law & Jue-Sheng Ong & Puya Gharahkhani & Pierre Fontanillas & Catherine M. Olsen & David C. Whiteman & Stuart MacGregor, 2022. "A multi-phenotype analysis reveals 19 susceptibility loci for basal cell carcinoma and 15 for squamous cell carcinoma," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    24. Melanie Goisauf & Kaya Akyüz & Gillian M. Martin, 2020. "Moving back to the future of big data-driven research: reflecting on the social in genomics," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-9, December.
    25. Gianmarco Mignogna & Caitlin E. Carey & Robbee Wedow & Nikolas Baya & Mattia Cordioli & Nicola Pirastu & Rino Bellocco & Kathryn Fiuza Malerbi & Michel G. Nivard & Benjamin M. Neale & Raymond K. Walte, 2023. "Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci," Nature Human Behaviour, Nature, vol. 7(8), pages 1371-1387, August.
    26. Kieron J. Barclay & Martin Hällsten, 2019. "Socioeconomic variation in child educational and socioeconomic attainment after parental death in Sweden," MPIDR Working Papers WP-2019-008, Max Planck Institute for Demographic Research, Rostock, Germany.
    27. Cornelius A Rietveld & Ronald de Vlaming & Eric A W Slob, 2023. "The identification of mediating effects using genome-based restricted maximum likelihood estimation," PLOS Genetics, Public Library of Science, vol. 19(2), pages 1-17, February.
    28. Michaela Paffenholz, 2023. "Adolescents’ Mental Health and Human Capital: The Role of Socioeconomic Rank," CESifo Working Paper Series 10248, CESifo.
    29. Liang, X.; & Sanderson, E.; & Windmeijer, F.;, 2022. "Selecting Valid Instrumental Variables in Linear Models with Multiple Exposure Variables: Adaptive Lasso and the Median-of-Medians Estimator," Health, Econometrics and Data Group (HEDG) Working Papers 22/22, HEDG, c/o Department of Economics, University of York.
    30. Jung, Dawoon & Lee, Jinkook & Meijer, Erik, 2022. "Revisiting the effect of retirement on Cognition: Heterogeneity and endowment," The Journal of the Economics of Ageing, Elsevier, vol. 21(C).
    31. Evelina T. Akimova & Tobias Wolfram & Xuejie Ding & Felix C. Tropf & Melinda C. Mills, 2025. "Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank," Nature Human Behaviour, Nature, vol. 9(2), pages 391-405, February.
    32. Gerard J. van den Berg & Stephanie von Hinke & Nicolai Vitt, 2023. "Early life exposure to measles and later-life outcomes: Evidence from the introduction of a vaccine," Bristol Economics Discussion Papers 23/776, School of Economics, University of Bristol, UK.
    33. Hans Kippersluis & Pietro Biroli & Rita Dias Pereira & Titus J. Galama & Stephanie Hinke & S. Fleur W. Meddens & Dilnoza Muslimova & Eric A. W. Slob & Ronald Vlaming & Cornelius A. Rietveld, 2023. "Overcoming attenuation bias in regressions using polygenic indices," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    34. Nagel, Mats, 2020. "Changing perspectives: Towards detailed phenotyping in genetics," Thesis Commons a4nz2, Center for Open Science.
    35. Barban, Nicola & De Cao, Elisabetta & Oreffice, Sonia & Quintana-Domeque, Climent, 2021. "The effect of education on spousal education: A genetic approach," Labour Economics, Elsevier, vol. 71(C).
    36. Bierut, Laura & Biroli, Pietro & Galama, Titus J. & Thom, Kevin, 2023. "Challenges in studying the interplay of genes and environment. A study of childhood financial distress moderating genetic predisposition for peak smoking," Journal of Economic Psychology, Elsevier, vol. 98(C).
    37. Jonsdottir, Gudrun A. & Einarsson, Gudmundur & Thorleifsson, Gudmar & Magnusson, Sigurdur H. & Gunnarsson, Arni F. & Frigge, Michael L. & Gisladottir, Rosa S. & Unnsteinsdottir, Unnur & Gunnarsson, Bj, 2021. "Genetic propensities for verbal and spatial ability have opposite effects on body mass index and risk of schizophrenia," Intelligence, Elsevier, vol. 88(C).
    38. Viinikainen, Jutta & Bryson, Alex & Böckerman, Petri & Kari, Jaana T. & Lehtimäki, Terho & Raitakari, Olli & Viikari, Jorma & Pehkonen, Jaakko, 2022. "Does better education mitigate risky health behavior? A mendelian randomization study," Economics & Human Biology, Elsevier, vol. 46(C).
    39. Lee, James J. & McGue, Matt & Iacono, William G. & Michael, Andrew M. & Chabris, Christopher F., 2019. "The causal influence of brain size on human intelligence: Evidence from within-family phenotypic associations and GWAS modeling," Intelligence, Elsevier, vol. 75(C), pages 48-58.
    40. Ronaldo N. Verano, PhD, 2024. "Level of Competence of Teachers in Filipino in the 2013 Filipino Orthography: Basis for Crafting Lesson Exemplars in Teaching Orthographic Rules," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(3s), pages 5548-5621, November.
    41. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    42. Robin Chark & Songfa Zhong & Shui Ying Tsang & Chiea Chuen Khor & Richard P. Ebstein & Hong Xue & Soo Hong Chew, 2022. "A gene–brain–behavior basis for familiarity bias in source preference," Theory and Decision, Springer, vol. 92(3), pages 531-567, April.
    43. Bhatnagar, Sahir R. & Lu, Tianyuan & Lovato, Amanda & Olds, David L. & Kobor, Michael S. & Meaney, Michael J. & O'Donnell, Kieran & Yang, Archer Y. & Greenwood, Celia M.T., 2023. "A sparse additive model for high-dimensional interactions with an exposure variable," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    44. Md. Moksedul Momin & Jisu Shin & Soohyun Lee & Buu Truong & Beben Benyamin & S. Hong Lee, 2023. "A method for an unbiased estimate of cross-ancestry genetic correlation using individual-level data," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    45. Abdellaoui, Abdel & Martin, Hilary C. & Rutherford, Adam & Kolk, Martin & Muthukrishna, Michael & Tropf, Felix & Mills, Melinda C. & Zietsch, Brendan & Verweij, Karin J.H. & Visscher, Peter M., 2025. "Socio-economic status is a social construct with heritable components and genetic consequences: a social construct with heritable components and genetic consequences," LSE Research Online Documents on Economics 127662, London School of Economics and Political Science, LSE Library.
    46. Hur, Yoon-Mi, 2020. "Relationships between cognitive abilities and prosocial behavior are entirely explained by shared genetic influences: A Nigerian twin study," Intelligence, Elsevier, vol. 82(C).
    47. Fletcher, Jason, 2023. "Decoupling genetics from attainments: The role of social environments," Economics & Human Biology, Elsevier, vol. 50(C).
    48. Evans, Linnea & Engelman, Michal & Mikulas, Alex & Malecki, Kristen, 2021. "How are social determinants of health integrated into epigenetic research? A systematic review," Social Science & Medicine, Elsevier, vol. 273(C).
    49. Jaakko Pehkonen & Jutta Viinikainen & Jaana T. Kari & Petri Böckerman & Terho Lehtimäki & Olli Raitakari, 2021. "Birth weight and adult income: An examination of mediation through adult height and body mass," Health Economics, John Wiley & Sons, Ltd., vol. 30(10), pages 2383-2398, September.
    50. Emil M. Pedersen & Esben Agerbo & Oleguer Plana-Ripoll & Jette Steinbach & Morten D. Krebs & David M. Hougaard & Thomas Werge & Merete Nordentoft & Anders D. Børglum & Katherine L. Musliner & Andrea G, 2023. "ADuLT: An efficient and robust time-to-event GWAS," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

  3. Magnus Johannesson & David I. Laibson & Sarah E. Medland & Michelle N. Meyer & Joseph K. Pickrell & Tõnu Esko & Robert F. Krueger & Jonathan P. Beauchamp & Philipp D. Koellinger & Daniel J. Benjamin &, 2016. "Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses," Post-Print hal-02017373, HAL.

    Cited by:

    1. Masahiro Matsunaga & Takahiko Masuda & Keiko Ishii & Yohsuke Ohtsubo & Yasuki Noguchi & Misaki Ochi & Hidenori Yamasue, 2018. "Culture and cannabinoid receptor gene polymorphism interact to influence the perception of happiness," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-17, December.
    2. Thomas Buser & Rafael Ahlskog & Magnus Johannesson & Sven Oskarsson, 2022. "Occupational sorting on genes," Tinbergen Institute Discussion Papers 22-062/I, Tinbergen Institute, revised 29 Mar 2023.
    3. David G. Blanchflower & Alex Bryson, 2021. "Taking the Pulse of Nations: a Biometric Measure of Well-being," NBER Working Papers 29587, National Bureau of Economic Research, Inc.
    4. Gueltzow, Maria & Lahtinen, Hannu & Bijlsma, Maarten J. & Myrskylä, Mikko & Martikainen, Pekka, 2024. "Genetic propensity to depression and the role of partnership status," Social Science & Medicine, Elsevier, vol. 351(C).
    5. Alfonso Flores-Lagunes & Amin Vikesh & Carlos A. Flores, 2019. "The Impact of BMI on Mental Health: Further Evidence from Genetic Markers," Center for Policy Research Working Papers 216, Center for Policy Research, Maxwell School, Syracuse University.
    6. Menta, Giorgia & Lepinteur, Anthony & Clark, Andrew E. & Ghislandi, Simone & D'Ambrosio, Conchita, 2023. "Maternal genetic risk for depression and child human capital," Journal of Health Economics, Elsevier, vol. 87(C).
    7. Giorgia Menta & Anthony Lepinteur & Andrew E Clark & Simone Ghislandi & Conchita d'Ambrosio, 2021. "Maternal depression and child human capital: A genetic instrumental-variable approach," PSE Working Papers halshs-03157270, HAL.
    8. Margot P. Weijer & Dirk H. M. Pelt & Lianne P. Vries & Bart M. L. Baselmans & Meike Bartels, 2022. "A Re-evaluation of Candidate Gene Studies for Well-Being in Light of Genome-Wide Evidence," Journal of Happiness Studies, Springer, vol. 23(6), pages 3031-3053, August.
    9. Carcaba, Ana & Arrondo, Ruben & Gonzalez, Eduardo, 2022. "Does good local governance improve subjective well-being?," MPRA Paper 123247, University Library of Munich, Germany.
    10. Mohsen Joshanloo, 2022. "Longitudinal Relations Between Depressive Symptoms and Life Satisfaction Over 15 Years," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 17(5), pages 3115-3130, October.
    11. Alexander Neumann & Ilja M Nolte & Irene Pappa & Tarunveer S Ahluwalia & Erik Pettersson & Alina Rodriguez & Andrew Whitehouse & Catharina E M van Beijsterveldt & Beben Benyamin & Anke R Hammerschlag , 2022. "A genome-wide association study of total child psychiatric problems scores," PLOS ONE, Public Library of Science, vol. 17(8), pages 1-23, August.
    12. Buser, Thomas & Ahlskog, Rafael & Johannesson, Magnus & Koellinger, Philipp & Oskarsson, Sven, 2024. "The causal effect of genetic variants linked to cognitive and non-cognitive skills on education and labor market outcomes," Labour Economics, Elsevier, vol. 90(C).
    13. Yingying Jiang & Chan Lu & Jing Chen & Yufeng Miao & Yuguo Li & Qihong Deng, 2022. "Happiness in University Students: Personal, Familial, and Social Factors: A Cross-Sectional Questionnaire Survey," IJERPH, MDPI, vol. 19(8), pages 1-12, April.
    14. Arrondo, Ruben & Carcaba, Ana & Gonzalez, Eduardo, 2021. "Drivers of Subjective Well-Being Under Different Economic Scenarios," MPRA Paper 123249, University Library of Munich, Germany.
    15. Das, Aniruddha, 2019. "Genes, depressive symptoms, and chronic stressors: A nationally representative longitudinal study in the United States," Social Science & Medicine, Elsevier, vol. 242(C).
    16. Nagel, Mats, 2020. "Changing perspectives: Towards detailed phenotyping in genetics," Thesis Commons a4nz2, Center for Open Science.
    17. Lianne P. Vries & Bart M. L. Baselmans & Meike Bartels, 2021. "Smartphone-Based Ecological Momentary Assessment of Well-Being: A Systematic Review and Recommendations for Future Studies," Journal of Happiness Studies, Springer, vol. 22(5), pages 2361-2408, June.
    18. Priya Gupta & Marco Galimberti & Yue Liu & Sarah Beck & Aliza Wingo & Thomas Wingo & Keyrun Adhikari & Henry R. Kranzler & Murray B. Stein & Joel Gelernter & Daniel F. Levey, 2024. "A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology," Nature Human Behaviour, Nature, vol. 8(11), pages 2235-2249, November.
    19. Viinikainen, Jutta & Bryson, Alex & Böckerman, Petri & Kari, Jaana T. & Lehtimäki, Terho & Raitakari, Olli & Viikari, Jorma & Pehkonen, Jaakko, 2022. "Does better education mitigate risky health behavior? A mendelian randomization study," Economics & Human Biology, Elsevier, vol. 46(C).
    20. Bernd Lachmann & Anna Doebler & Cornelia Sindermann & Rayna Sariyska & Andrew Cooper & Heidrun Haas & Christian Montag, 2021. "The Molecular Genetics of Life Satisfaction: Extending Findings from a Recent Genome-Wide Association Study and Examining the Role of the Serotonin Transporter," Journal of Happiness Studies, Springer, vol. 22(1), pages 305-322, January.
    21. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    22. Carcaba, Ana & Gonzalez, Eduardo & Arrondo, Ruben, 2023. "Effects of the political configuration of local governments on subjective well-being," MPRA Paper 123248, University Library of Munich, Germany.
    23. Andrea G Allegrini & Ville Karhunen & Jonathan R I Coleman & Saskia Selzam & Kaili Rimfeld & Sophie von Stumm & Jean-Baptiste Pingault & Robert Plomin, 2020. "Multivariable G-E interplay in the prediction of educational achievement," PLOS Genetics, Public Library of Science, vol. 16(11), pages 1-20, November.
    24. Xuefeng Li & Han Yang & Jin Jia, 2022. "Impact of energy poverty on cognitive and mental health among middle-aged and older adults in China," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-13, December.
    25. Ana Cárcaba & Eduardo González, 2024. "The relationship between income and subjective well-being: the case of Spain," Economics and Business Letters, Oviedo University Press, vol. 13(4), pages 203-212.

  4. Groenen, P.J.F. & Terada, Y., 2015. "Symbolic Multidimensional Scaling," Econometric Institute Research Papers EI 2015-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Pełka Marcin, 2019. "Assessment of the Development of the European Oecd Countries with the Application of Linear Ordering and Ensemble Clustering of Symbolic Data," Folia Oeconomica Stetinensia, Sciendo, vol. 19(2), pages 117-133, December.

  5. Michael Greenacre, 2015. "Weighted Euclidean Biplots," Working Papers 708, Barcelona School of Economics.

    Cited by:

    1. Fry, J.T. & Slifko, Matt & Leman, Scotland, 2018. "Generalized biplots for stress-based multidimensionally scaled projections," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 340-353.
    2. Giuseppe Bove & Akinori Okada, 2018. "Methods for the analysis of asymmetric pairwise relationships," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 5-31, March.
    3. Federico Gobbo, 2017. "Beyond the Nation-State? The Ideology of the Esperanto Movement between Neutralism and Multilingualism," Social Inclusion, Cogitatio Press, vol. 5(4), pages 38-47.

  6. Peter Exterkate & Patrick J.F. Groenen & Christiaan Heij & Dick van Dijk, 2013. "Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression," CREATES Research Papers 2013-16, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Thierry Moudiki & Frédéric Planchet & Areski Cousin, 2018. "Multiple Time Series Forecasting Using Quasi-Randomized Functional Link Neural Networks," Post-Print hal-02055155, HAL.
    2. Alessandro Giovannelli, 2012. "Nonlinear Forecasting Using Large Datasets: Evidences on US and Euro Area Economies," CEIS Research Paper 255, Tor Vergata University, CEIS, revised 08 Nov 2012.
    3. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
    4. Rajveer Jat & Daanish Padha, 2024. "Kernel Three Pass Regression Filter," Papers 2405.07292, arXiv.org, revised Feb 2025.
    5. A. Frenkel’ A. & N. Volkova N. & A. Surkov A. & E. Romanyuk I. & А. Френкель А. & Н. Волкова Н. & А. Сурков А. & Э. Романюк И., 2018. "Использование Методов Гребневой Регрессии При Объединении Прогнозов // The Application Of Ridge Regression Methods When Combining Forecasts," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(4), pages 6-17.
    6. Oslandsbotn, Andreas & Kereta, Željko & Naumova, Valeriya & Freund, Yoav & Cloninger, Alexander, 2022. "StreaMRAK a streaming multi-resolution adaptive kernel algorithm," Applied Mathematics and Computation, Elsevier, vol. 426(C).
    7. Abolghasemi, Mahdi & Abbasi, Babak & HosseiniFard, Zahra, 2025. "Machine learning for satisficing operational decision making: A case study in blood supply chain," International Journal of Forecasting, Elsevier, vol. 41(1), pages 3-19.
    8. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    9. Wei, Yu & Liang, Chao & Li, Yan & Zhang, Xunhui & Wei, Guiwu, 2020. "Can CBOE gold and silver implied volatility help to forecast gold futures volatility in China? Evidence based on HAR and Ridge regression models," Finance Research Letters, Elsevier, vol. 35(C).
    10. Peter Exterkate, 2012. "Model Selection in Kernel Ridge Regression," CREATES Research Papers 2012-10, Department of Economics and Business Economics, Aarhus University.
    11. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    12. Tian Han & Ying Wang & Xiao Wang & Kang Chen & Huaiwu Peng & Zhenxin Gao & Lanxin Cui & Wentong Sun & Qinke Peng, 2023. "Mixed Multi-Pattern Regression for DNI Prediction in Arid Desert Areas," Sustainability, MDPI, vol. 15(17), pages 1-16, August.
    13. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    14. Daiki Maki & Yasushi Ota, 2019. "Robust tests for ARCH in the presence of the misspecified conditional mean: A comparison of nonparametric approches," Papers 1907.12752, arXiv.org, revised Sep 2019.
    15. Kutateladze, Varlam, 2022. "The kernel trick for nonlinear factor modeling," International Journal of Forecasting, Elsevier, vol. 38(1), pages 165-177.
    16. Varlam Kutateladze, 2021. "The Kernel Trick for Nonlinear Factor Modeling," Papers 2103.01266, arXiv.org.
    17. Milan Fičura, 2019. "Forecasting Foreign Exchange Rate Movements with k-Nearest-Neighbour, Ridge Regression and Feed-Forward Neural Networks," FFA Working Papers 1.001, Prague University of Economics and Business, revised 24 Nov 2019.
    18. Cheng, Kai & Lu, Zhenzhou, 2018. "Sparse polynomial chaos expansion based on D-MORPH regression," Applied Mathematics and Computation, Elsevier, vol. 323(C), pages 17-30.
    19. Saeed Salah & Husain R. Alsamamra & Jawad H. Shoqeir, 2022. "Exploring Wind Speed for Energy Considerations in Eastern Jerusalem-Palestine Using Machine-Learning Algorithms," Energies, MDPI, vol. 15(7), pages 1-16, April.
    20. Christophe Croux & Peter Exterkate, 2011. "Sparse and Robust Factor Modelling," Tinbergen Institute Discussion Papers 11-122/4, Tinbergen Institute.
    21. Yoshiki Nakajima & Naoya Sueishi, 2022. "Forecasting the Japanese macroeconomy using high-dimensional data," The Japanese Economic Review, Springer, vol. 73(2), pages 299-324, April.
    22. Peter Exterkate, 2011. "Modelling Issues in Kernel Ridge Regression," Tinbergen Institute Discussion Papers 11-138/4, Tinbergen Institute.
    23. Wojciech Victor Fulmyk, 2023. "Nonlinear Granger Causality using Kernel Ridge Regression," Papers 2309.05107, arXiv.org.

  7. Schoonees, P.C. & van de Velden, M. & Groenen, P.J.F., 2013. "Constrained Dual Scaling for Detecting Response Styles in Categorical Data," Econometric Institute Research Papers EI 2013-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Pieter C. Schoonees & Patrick J. F. Groenen & Michel Velden, 2022. "Least-squares bilinear clustering of three-way data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(4), pages 1001-1037, December.

  8. Rietveld, C.A. & Groenen, P.J.F. & Koellinger, Ph.D. & van der Loos, M.J.H.M. & Thurik, A.R., 2013. "Living Forever: Entrepreneurial Overconfidence at Older Ages," ERIM Report Series Research in Management ERS-2013-012-STR, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Viktorija Ilieva & Thomas Brudermann & Ljubomir Drakulevski, 2018. "“Yes, we know!” (Over)confidence in general knowledge among Austrian entrepreneurs," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-15, May.
    2. Martin Koudstaal & Randolph Sloof & Mirjam van Praag, 2015. "Are Entrepreneurs more Optimistic and Overconfident than Managers and Employees?," Tinbergen Institute Discussion Papers 15-124/VII, Tinbergen Institute.
    3. Jahangir Yadollahi Farsi & Pouria Nouri & Abdolah Ahmadi Kafeshani, 2016. "Identifying Decision Making Biases in Entrepreneurial Opportunity Exploitation Decisions," International Business Research, Canadian Center of Science and Education, vol. 9(5), pages 158-163, May.
    4. Kambiz Talebi & Pouria Nouri & Abdolah Ahmadi Kafeshani, 2014. "Identifying the main Individual Factors Influencing Entrepreneurial Decision making Biases: A Qualitative Content Analysis Approach," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 4(8), pages 1-11, August.
    5. Jahangir Yadollahi Farsi & Pouria Nouri & Abdolah Ahmadi Kafeshani & Mohamad Taghi Toghraee, 2014. "Identifying the Main Factors Influencing the Formation of Overconfidence Bias in Entrepreneurs: A Qualitative Content Analysis Approach," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 4(4), pages 456-469, April.
    6. Indy Bernoster & Cornelius A. Rietveld & A. Roy Thurik & Olivier Torrès, 2018. "Overconfidence, Optimism and Entrepreneurship," Sustainability, MDPI, vol. 10(7), pages 1-14, June.

  9. Hastie, Nicholas D. & van der Loos, Matthijs J. H. M. & Vitart, Veronique & Völzke, Henry & Wellmann, Jürgen & Yu, Lei & Zhao, Wei & Allik, Jüri & Attia, John R. & Bandinelli, Stefania & Bastardot,, 2013. "GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment," Scholarly Articles 13383543, Harvard University Department of Economics.

    Cited by:

    1. De Neve, Jan-Emmanuel & Fowler, James H., 2014. "Credit card borrowing and the monoamine oxidase A (MAOA) gene," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 428-439.
    2. Milkman, Katherine L. & Beshears, John Leonard & Choi, James J. & Laibson, David I. & Madrian, Brigitte, 2015. "The Effect of Providing Peer Information on Retirement Savings Decisions," Scholarly Articles 32785047, Harvard University Department of Economics.
    3. Nicola Barban & Elisabetta De Cao & Sonia Oreffice, 2016. "Assortative Mating on Education: A Genetic Assessment," Economics Series Working Papers 791, University of Oxford, Department of Economics.
    4. Margherita Malanchini & Andrea G. Allegrini & Michel G. Nivard & Pietro Biroli & Kaili Rimfeld & Rosa Cheesman & Sophie Stumm & Perline A. Demange & Elsje Bergen & Andrew D. Grotzinger & Laurel Raffin, 2024. "Genetic associations between non-cognitive skills and academic achievement over development," Nature Human Behaviour, Nature, vol. 8(10), pages 2034-2046, October.
    5. Thomas Buser & Rafael Ahlskog & Magnus Johannesson & Sven Oskarsson, 2022. "Occupational sorting on genes," Tinbergen Institute Discussion Papers 22-062/I, Tinbergen Institute, revised 29 Mar 2023.
    6. A. Roy Thurik & David B. Audretsch & Jörn H. Block & Andrew Burke & Martin A. Carree & Marcus Dejardin & Cornelius A. Rietveld & Mark Sanders & Ute Stephan & Johan Wiklund, 2024. "The impact of entrepreneurship research on other academic fields," Small Business Economics, Springer, vol. 62(2), pages 727-751, February.
    7. Wei, Xu & Zhou, Yi & Zhou, Yimin, 2022. "Signaling of earlier-born Children's endowments, intra-household allocation, and birth-order effects," Economic Modelling, Elsevier, vol. 108(C).
    8. Pehkonen, Jaakko & Viinikainen, Jutta & Böckerman, Petri & Lehtimäki, Terho & Pitkänen, Niina & Raitakari, Olli, 2017. "Genetic endowments, parental resources and adult health: Evidence from the Young Finns Study," Social Science & Medicine, Elsevier, vol. 188(C), pages 191-200.
    9. Akimova, Evelina T. & Wolfram, Tobias & Ding, Xuejie & Tropf, Felix C. & Mills, Melinda C., 2025. "Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 9(Febuary), pages 391-405.
    10. Quamrul H. Ashraf & Oded Galor, 2018. "The Macrogenoeconomics of Comparative Development," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 1119-1155, September.
    11. Lauren L. Schmitz & Dalton Conley, 2016. "The Effect of Vietnam-Era Conscription and Genetic Potential for Educational Attainment on Schooling Outcomes," NBER Working Papers 22393, National Bureau of Economic Research, Inc.
    12. Hilger, Kirsten & Spinath, Frank M. & Troche, Stefan & Schubert, Anna-Lena, 2022. "The biological basis of intelligence: Benchmark findings," Intelligence, Elsevier, vol. 93(C).
    13. Daniel Barth & Nicholas W. Papageorge & Kevin Thom, 2018. "Genetic Endowments and Wealth Inequality," Working Papers 2018-077, Human Capital and Economic Opportunity Working Group.
    14. Victor Ronda & Esben Agerbo & Dorthe Bleses & Preben Bo Mortensen & Anders Børglum & Ole Mors & Michael Rosholm & David M. Hougaard & Merete Nordentoft & Thomas Werge, 2022. "Family disadvantage, gender, and the returns to genetic human capital," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(2), pages 550-578, April.
    15. Nicholas W. Papageorge & Kevin Thom, 2018. "Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study," Working Papers 2018-076, Human Capital and Economic Opportunity Working Group.
    16. Pereira, Rita & Biroli, Pietro & von hinke, stephanie & Van Kippersluis, Hans & Galama, Titus & Rietveld, Niels & Thom, Kevin, 2022. "Gene-Environment Interplay in the Social Sciences," OSF Preprints d96z3, Center for Open Science.
    17. Chabris, C. F. & Lee, J. J. & Cesarini, D. & Benjamin, D. J. & Laibson, David I., 2015. "The Fourth Law of Behavior Genetics," Scholarly Articles 30780203, Harvard University Department of Economics.
    18. Papaioannou, Sotiris, 2018. "Does education affect economic liberty? The role of information and the media," MPRA Paper 87417, University Library of Munich, Germany, revised 16 Jun 2018.
    19. Felix C. Tropf & Jornt J. Mandemakers, 2017. "Is the Association Between Education and Fertility Postponement Causal? The Role of Family Background Factors," Demography, Springer;Population Association of America (PAA), vol. 54(1), pages 71-91, February.
    20. Tzu-Ting Chen & Jaeyoung Kim & Max Lam & Yi-Fang Chuang & Yen-Ling Chiu & Shu-Chin Lin & Sang-Hyuk Jung & Beomsu Kim & Soyeon Kim & Chamlee Cho & Injeong Shim & Sanghyeon Park & Yeeun Ahn & Aysu Okbay, 2024. "Shared genetic architectures of educational attainment in East Asian and European populations," Nature Human Behaviour, Nature, vol. 8(3), pages 562-575, March.
    21. Fatemeh Bahador & Ayyub Sheikhi & Alireza Arabpour, 2024. "A two-stage Bridge estimator for regression models with endogeneity based on control function method," Computational Statistics, Springer, vol. 39(3), pages 1351-1370, May.
    22. Casper A.P. Burik & Hyeokmoon Kweon & Philipp D. Koellinger, 2021. "Disparities in socio-economic status and BMI in the UK are partly due to genetic and environmental luck," Tinbergen Institute Discussion Papers 21-035/V, Tinbergen Institute.
    23. Buser, Thomas & Ahlskog, Rafael & Johannesson, Magnus & Koellinger, Philipp & Oskarsson, Sven, 2024. "The causal effect of genetic variants linked to cognitive and non-cognitive skills on education and labor market outcomes," Labour Economics, Elsevier, vol. 90(C).
    24. Tropf, Felix C & Mandemakers, Jornt J, 2017. "Is the Association Between Education and Fertility Postponement Causal? The Role of Family Background Factors," OSF Preprints dqrrx, Center for Open Science.
    25. Rietveld, Cornelius A. & Webbink, Dinand, 2016. "On the genetic bias of the quarter of birth instrument," Economics & Human Biology, Elsevier, vol. 21(C), pages 137-146.
    26. Cook, C. Justin & Fletcher, Jason M., 2015. "Can education rescue genetic liability for cognitive decline?," Social Science & Medicine, Elsevier, vol. 127(C), pages 159-170.
    27. Juan Gabriel Rodríguez, 2022. "Making the most of world talent for science? The Nobel Prize and Fields Medal experience," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 813-847, February.
    28. Baier, Tina & Lyngstad, Torkild Hovde, 2024. "Social Background Effects on Educational Outcomes - New Insights from Modern Genetic Science," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 76(3), pages 525-545.
    29. Evelina T. Akimova & Tobias Wolfram & Xuejie Ding & Felix C. Tropf & Melinda C. Mills, 2025. "Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank," Nature Human Behaviour, Nature, vol. 9(2), pages 391-405, February.
    30. Fukushima, Nanna & von Hinke, Stephanie & Sørensen, Emil N., 2024. "The Long-Term Human Capital and Health Impacts of a Pollution Reduction Programme," IZA Discussion Papers 17205, Institute of Labor Economics (IZA).
    31. Pascal Schlosser & Adrienne Tin & Pamela R. Matias-Garcia & Chris H. L. Thio & Roby Joehanes & Hongbo Liu & Antoine Weihs & Zhi Yu & Anselm Hoppmann & Franziska Grundner-Culemann & Josine L. Min & Ade, 2021. "Meta-analyses identify DNA methylation associated with kidney function and damage," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
    32. Steven F. Lehrer & Weili Ding, 2017. "Are genetic markers of interest for economic research?," IZA Journal of Labor Policy, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 6(1), pages 1-23, December.
    33. Barban, Nicola & De Cao, Elisabetta & Oreffice, Sonia & Quintana-Domeque, Climent, 2021. "The effect of education on spousal education: A genetic approach," Labour Economics, Elsevier, vol. 71(C).
    34. Boardman, Jason D. & Domingue, Benjamin W. & Daw, Jonathan, 2015. "What can genes tell us about the relationship between education and health?," Social Science & Medicine, Elsevier, vol. 127(C), pages 171-180.
    35. von Hinke, Stephanie & Davey Smith, George & Lawlor, Debbie A. & Propper, Carol & Windmeijer, Frank, 2016. "Genetic markers as instrumental variables," Journal of Health Economics, Elsevier, vol. 45(C), pages 131-148.
    36. Junhao Wen & Bingxin Zhao & Zhijian Yang & Guray Erus & Ioanna Skampardoni & Elizabeth Mamourian & Yuhan Cui & Gyujoon Hwang & Jingxuan Bao & Aleix Boquet-Pujadas & Zhen Zhou & Yogasudha Veturi & Mary, 2024. "The genetic architecture of multimodal human brain age," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    37. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    38. Hamermesh, Daniel S. & Zhang, Anwen, 2024. "The Economic Impact of Heritable Physical Traits: Hot Parents, Rich Kid?," IZA Discussion Papers 16742, Institute of Labor Economics (IZA).
    39. Bhatnagar, Sahir R. & Lu, Tianyuan & Lovato, Amanda & Olds, David L. & Kobor, Michael S. & Meaney, Michael J. & O'Donnell, Kieran & Yang, Archer Y. & Greenwood, Celia M.T., 2023. "A sparse additive model for high-dimensional interactions with an exposure variable," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    40. Daniel J. Benjamin & David Cesarini & Patrick Turley & Alexander Strudwick Young, 2024. "Social-Science Genomics: Progress, Challenges, and Future Directions," NBER Working Papers 32404, National Bureau of Economic Research, Inc.
    41. Becker, David & Bakhiet, Salaheldin Farah & Alshahomee, Alsedig Abdalgadr & Gadour, Abdelbasit & Elmenfi, Fadil & Essa, Yossry Ahmed Sayed & Dutton, Edward, 2023. "Opinions on intelligence: An Arab perspective," Intelligence, Elsevier, vol. 97(C).
    42. Daiji Kawaguchi & Jungmin Lee & Ming‐Jen Lin & Izumi Yokoyama, 2023. "Is Asian flushing syndrome a disadvantage in the labor market?," Health Economics, John Wiley & Sons, Ltd., vol. 32(7), pages 1478-1503, July.
    43. Tiago Neves Sequeira & Marcelo Santos & Alexandra Ferreira-Lopes, 2019. "Human capital and genetic diversity," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 9(3), pages 311-330, September.
    44. Abdellaoui, Abdel & Martin, Hilary C. & Rutherford, Adam & Kolk, Martin & Muthukrishna, Michael & Tropf, Felix & Mills, Melinda C. & Zietsch, Brendan & Verweij, Karin J.H. & Visscher, Peter M., 2025. "Socio-economic status is a social construct with heritable components and genetic consequences: a social construct with heritable components and genetic consequences," LSE Research Online Documents on Economics 127662, London School of Economics and Political Science, LSE Library.
    45. Yi Zeng & Huashuai Chen & Xiaomin Liu & Rui Ye & Enjun Xie & Zhihua Chen & Jiehua Lu & Jianxin Li & Yaohua Tian & Ting Ni & Lars Bolund & Kenneth C. Land & Anatoliy Yashin & Angela M. O'Rand & Liang S, 2017. "Sex differences in genetic associations with longevity in Han Chinese: sex-stratified genome-wide association study and polygenic risk score analysis," MPIDR Working Papers WP-2017-004, Max Planck Institute for Demographic Research, Rostock, Germany.

  10. van de Velden, M. & de Beuckelaer, A. & Groenen, P.J.F. & Busing, F.M.T.A., 2011. "Nonmetric Unfolding of Marketing Data: Degeneracy and Stability," ERIM Report Series Research in Management ERS-2011-006-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Lam, K.Y. & van de Velden, M. & Franses, Ph.H.B.F., 2011. "Visualizing attitudes towards service levels," ERIM Report Series Research in Management ERS-2011-022-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  11. van der Loos, M.J.H.M. & Koellinger, Ph.D. & Groenen, P.J.F. & Thurik, A.R., 2010. "Genome-wide Association Studies and the Genetics of Entrepreneurship," ERIM Report Series Research in Management ERS-2010-004-ORG, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. A. Roy Thurik & David B. Audretsch & Jörn H. Block & Andrew Burke & Martin A. Carree & Marcus Dejardin & Cornelius A. Rietveld & Mark Sanders & Ute Stephan & Johan Wiklund, 2024. "The impact of entrepreneurship research on other academic fields," Small Business Economics, Springer, vol. 62(2), pages 727-751, February.
    2. Matthijs J H M van der Loos & Cornelius A Rietveld & Niina Eklund & Philipp D Koellinger & Fernando Rivadeneira & Gonçalo R Abecasis & Georgina A Ankra-Badu & Sebastian E Baumeister & Daniel J Benjami, 2013. "The Molecular Genetic Architecture of Self-Employment," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    3. Naudé, Wim & Amoros, José Ernesto & Cristi, Oscar, 2012. ""Surfeiting, the appetite may sicken": Entrepreneurship and the happiness of nations," MERIT Working Papers 2012-013, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    4. Matthijs Loos & Philipp Koellinger & Patrick Groenen & Cornelius Rietveld & Fernando Rivadeneira & Frank Rooij & André Uitterlinden & Albert Hofman & A. Thurik, 2011. "Candidate gene studies and the quest for the entrepreneurial gene," Small Business Economics, Springer, vol. 37(3), pages 269-275, October.
    5. Hyytinen, Ari & Ilmakunnas, Pekka & Toivanen, Otto, 2013. "The return-to-entrepreneurship puzzle," Labour Economics, Elsevier, vol. 20(C), pages 57-67.
    6. Singer Burton, 2011. "Genome-Phenome Linkages in Human Population Surveys, with Special Emphasis on the Health and Retirement Survey," Forum for Health Economics & Policy, De Gruyter, vol. 14(2), pages 1-24, April.
    7. Rafael Ravina-Ripoll & María-José Foncubierta-Rodríguez & Eduardo Ahumada-Tello & Luis Bayardo Tobar-Pesantez, 2021. "Does Entrepreneurship Make You Happier? A Comparative Analysis between Entrepreneurs and Wage Earners," Sustainability, MDPI, vol. 13(18), pages 1-19, September.
    8. Philipp Koellinger & Matthijs Loos & Patrick Groenen & A. Thurik & Fernando Rivadeneira & Frank Rooij & André Uitterlinden & Albert Hofman, 2010. "Genome-wide association studies in economics and entrepreneurship research: promises and limitations," Small Business Economics, Springer, vol. 35(1), pages 1-18, July.
    9. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    10. Lerner, Daniel A. & Hatak, Isabella & Rauch, Andreas, 2018. "Deep roots? Behavioral Inhibition and Behavioral Activation System (BIS/BAS) sensitivity and entrepreneurship," Journal of Business Venturing Insights, Elsevier, vol. 9(C), pages 107-115.
    11. Wim Naudé & José Amorós & Oscar Cristi, 2014. "“Surfeiting, the appetite may sicken”: entrepreneurship and happiness," Small Business Economics, Springer, vol. 42(3), pages 523-540, March.

  12. Exterkate, P. & van Dijk, D.J.C. & Heij, C. & Groenen, P.J.F., 2010. "Forecasting the Yield Curve in a Data-Rich Environment using the Factor-Augmented Nelson-Siegel Model," Econometric Institute Research Papers EI 2010-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    2. Bräuning, Falk & Koopman, Siem Jan, 2014. "Forecasting macroeconomic variables using collapsed dynamic factor analysis," International Journal of Forecasting, Elsevier, vol. 30(3), pages 572-584.
    3. Dick Dijk & Siem Jan Koopman & Michel Wel & Jonathan H. Wright, 2014. "Forecasting interest rates with shifting endpoints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 693-712, August.
    4. Adam Traczyk, 2013. "Financial integration and the term structure of interest rates," Empirical Economics, Springer, vol. 45(3), pages 1267-1305, December.
    5. Michele Manna & Emmanuela Bernardini & Mauro Bufano & Davide Dottori, 2013. "Modelling public debt strategies," Questioni di Economia e Finanza (Occasional Papers) 199, Bank of Italy, Economic Research and International Relations Area.
    6. Fausto Vieira & Fernando Chague, Marcelo Fernandes, 2016. "A dynamic Nelson-Siegel model with forward-looking indicators for the yield curve in the US," Working Papers, Department of Economics 2016_31, University of São Paulo (FEA-USP).
    7. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    8. Oguzhan Cepni & Ibrahim Ethem Guney & Doruk Kucuksarac & Muhammed Hasan Yilmaz, 2020. "Do Local and Global Factors Impact the Emerging Markets’s Sovereign Yield Curves? Evidence from a Data-Rich Environment," Working Papers 2004, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    9. Scott A. Brave & R. Andrew Butters & David Kelley, 2019. "A New “Big Data” Index of U.S. Economic Activity," Economic Perspectives, Federal Reserve Bank of Chicago, issue 1, pages 1-30.
    10. Fausto Vieira & Fernando Chague & Marcelo Fernandes, 2016. "Forecasting the Brazilian Yield Curve Using Forward-Looking Variables," Working Papers 799, Queen Mary University of London, School of Economics and Finance.
    11. Siem Jan Koopman & Michel van der Wel, 2011. "Forecasting the U.S. Term Structure of Interest Rates using a Macroeconomic Smooth Dynamic Factor Model," Tinbergen Institute Discussion Papers 11-063/4, Tinbergen Institute.
    12. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
    13. Oguzhan Cepni & Ibrahim Ethem Guney & Doruk Kucuksarac & Muhammed Hasan Yilmaz, 2018. "The Interaction between Yield Curve and Macroeconomic Factors," CBT Research Notes in Economics 1802, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    14. Caio Almeida & Axel Simonsen & José Valentim Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.
    15. Gerhart, Christoph & Lütkebohmert, Eva, 2020. "Empirical analysis and forecasting of multiple yield curves," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 59-78.
    16. Massimo Guidolin & Daniel L. Thornton, 2010. "Predictions of short-term rates and the expectations hypothesis," Working Papers 2010-013, Federal Reserve Bank of St. Louis.
    17. Lorenčič Eva, 2016. "Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve," Naše gospodarstvo/Our economy, Sciendo, vol. 62(2), pages 42-50, June.
    18. Aránzazu Juan & Pilar Poncela & Esther Ruiz, 2025. "Economic activity and $$\hbox {CO}_2$$ CO 2 emissions in Spain," Empirical Economics, Springer, vol. 68(3), pages 1379-1408, March.
    19. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2016. "What derives the bond portfolio value-at-risk: Information roles of macroeconomic and financial stress factors," SFB 649 Discussion Papers 2016-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. Eran Raviv, 2013. "Prediction Bias Correction for Dynamic Term Structure Models," Tinbergen Institute Discussion Papers 13-041/III, Tinbergen Institute.
    21. Norman R. Swanson & Weiqi Xiong & Xiye Yang, 2020. "Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 587-613, August.
    22. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.
    23. De Gooijer Jan G. & Zerom Dawit, 2020. "Penalized Averaging of Parametric and Non-Parametric Quantile Forecasts," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.

  13. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "Map Based Visualization of Product Catalogs," ERIM Report Series Research in Management ERS-2009-010-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Borg, I. & Groenen, P.J.F. & Jehn, K.A. & Bilsky, W. & Schwartz, S.H., 2009. "Embedding the Organizational Culture Profile into Schwartz’s Universal Value Theory using Multidimensional Scaling with Regional Restrictions," ERIM Report Series Research in Management ERS-2009-017-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  14. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "Determination of Attribute Weights for Recommender Systems Based on Product Popularity," ERIM Report Series Research in Management ERS-2009-022-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "An Empirical Comparison of Dissimilarity Measures for Recommender Systems," ERIM Report Series Research in Management ERS-2009-023-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  15. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2008. "Choosing Attribute Weights for Item Dissimilarity using Clikstream Data with an Application to a Product Catalog Map," ERIM Report Series Research in Management ERS-2008-024-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "An Empirical Comparison of Dissimilarity Measures for Recommender Systems," ERIM Report Series Research in Management ERS-2009-023-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "Determination of Attribute Weights for Recommender Systems Based on Product Popularity," ERIM Report Series Research in Management ERS-2009-022-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "Map Based Visualization of Product Catalogs," ERIM Report Series Research in Management ERS-2009-010-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  16. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2007. "A graphical shopping interface bases on product attributes," Econometric Institute Research Papers EI 2007-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "An Empirical Comparison of Dissimilarity Measures for Recommender Systems," ERIM Report Series Research in Management ERS-2009-023-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "Determination of Attribute Weights for Recommender Systems Based on Product Popularity," ERIM Report Series Research in Management ERS-2009-022-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "Map Based Visualization of Product Catalogs," ERIM Report Series Research in Management ERS-2009-010-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  17. van de Velden, M. & Groenen, P.J.F. & Poblome, J., 2007. "Seriation by constrained correspondence analysis: a simulation study," Econometric Institute Research Papers EI 2007-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Antonello D’Ambra & Pietro Amenta, 2011. "Correspondence Analysis with Linear Constraints of Ordinal Cross-Classifications," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 70-92, April.
    2. Schoonees, P.C., 2015. "Methods for Modelling Response Styles," ERIM Report Series Research in Management EPS–2015–348–MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Schoonees, P.C. & van de Velden, M. & Groenen, P.J.F., 2013. "Constrained Dual Scaling for Detecting Response Styles in Categorical Data," Econometric Institute Research Papers EI 2013-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Blasius, J. & Greenacre, M. & Groenen, P.J.F. & van de Velden, M., 2009. "Special issue on correspondence analysis and related methods," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3103-3106, June.
    5. D'Ambra, Luigi & Amenta, Pietro & D'Ambra, Antonello & de Tibeiro, Jules S., 2021. "A study of the family service expenditures and the socio-demographic characteristics via fixed marginals correspondence analysis," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).

  18. van Rosmalen, J.M. & van Herk, H. & Groenen, P.J.F., 2007. "Identifying Unknown Response Styles: A Latent-Class Bilinear Multinomial Logit Model," ERIM Report Series Research in Management ERS-2007-045-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Natalia Kieruj & Guy Moors, 2013. "Response style behavior: question format dependent or personal style?," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 193-211, January.

  19. Heij, C. & van Dijk, D.J.C. & Groenen, P.J.F., 2006. "Improved Construction of diffusion indexes for macroeconomic forecasting," Econometric Institute Research Papers EI 2006-03-REV, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Jorge L.M. Andraz & Pedro M.D.C.B. Gouveia & Paulo M.M. Rodrigues, 2009. "Modelling and Forecasting the UK Tourism Growth Cycle in Algarve," Tourism Economics, , vol. 15(2), pages 323-338, June.

  20. Heij, C. & Groenen, P.J.F. & van Dijk, D.J.C., 2006. "Time series forecasting by principal covariate regression," Econometric Institute Research Papers EI 2006-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Peter Exterkate & Dick Van Dijk & Christiaan Heij & Patrick J. F. Groenen, 2013. "Forecasting the Yield Curve in a Data‐Rich Environment Using the Factor‐Augmented Nelson–Siegel Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(3), pages 193-214, April.
    2. Heij, Christiaan & Groenen, Patrick J.F. & van Dijk, Dick, 2007. "Forecast comparison of principal component regression and principal covariate regression," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3612-3625, April.

  21. Nalbantov, G.I. & Groenen, P.J.F. & Bioch, J.C., 2006. "Nearest convex hull classification," Econometric Institute Research Papers EI 2006-50, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. James Chok & Geoffrey M. Vasil, 2023. "Convex optimization over a probability simplex," Papers 2305.09046, arXiv.org, revised Apr 2025.

  22. Groenen, P.J.F. & Kaymak, U. & van Rosmalen, J.M., 2006. "Fuzzy clustering with Minkowski distance," Econometric Institute Research Papers EI 2006-24, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Abder-Rahman Ali & Jingpeng Li & Sally Jane O’Shea, 2020. "Towards the automatic detection of skin lesion shape asymmetry, color variegation and diameter in dermoscopic images," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-21, June.

  23. Groenen, P.J.F. & Winsberg, S. & Rodriguez, O. & Diday, E., 2005. "SymScal: symbolic multidimensional scaling of interval dissimilarities," Econometric Institute Research Papers EI 2005-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Hebert, Pierre-Alexandre & Masson, Marie-Helene & Denoeux, Thierry, 2006. "Fuzzy multidimensional scaling," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 335-359, November.
    2. Pełka Marcin, 2019. "Assessment of the Development of the European Oecd Countries with the Application of Linear Ordering and Ensemble Clustering of Symbolic Data," Folia Oeconomica Stetinensia, Sciendo, vol. 19(2), pages 117-133, December.

  24. van Rosmalen, J.M. & Groenen, P.J.F. & Trejos, J. & Castilli, W., 2005. "Global Optimization strategies for two-mode clustering," Econometric Institute Research Papers EI 2005-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Jan Schepers & Eva Ceulemans & Iven Mechelen, 2008. "Selecting Among Multi-Mode Partitioning Models of Different Complexities: A Comparison of Four Model Selection Criteria," Journal of Classification, Springer;The Classification Society, vol. 25(1), pages 67-85, June.
    2. Vera, J. Fernando & Macas, Rodrigo & Heiser, Willem J., 2009. "A dual latent class unfolding model for two-way two-mode preference rating data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3231-3244, June.

  25. Bioch, J.C. & Groenen, P.J.F. & Nalbantov, G.I., 2005. "Solving and interpreting binary classification problems in marketing with SVMs," Econometric Institute Research Papers EI 2005-46, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Andrey Zahariev & Mikhail Zveryаkov & Stoyan Prodanov & Galina Zaharieva & Petko Angelov & Silvia Zarkova & Mariana Petrova, 2020. "Debt management evaluation through Support Vector Machines: on the example of Italy and Greece," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(3), pages 2382-2393, March.

  26. Raoul Pietersz & Patrick J. F. Groenen, 2005. "Rank Reduction of Correlation Matrices by Majorization," Finance 0502006, University Library of Munich, Germany.

    Cited by:

    1. Kohei Adachi, 2011. "Constrained principal component analysis of standardized data for biplots with unit-length variable vectors," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(1), pages 23-36, April.
    2. Raoul Pietersz & Antoon Pelsser, 2005. "A Comparison of Single Factor Markov-functional and Multi Factor Market Models," Finance 0502008, University Library of Munich, Germany.
    3. Hebert, Pierre-Alexandre & Masson, Marie-Helene & Denoeux, Thierry, 2006. "Fuzzy multidimensional scaling," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 335-359, November.
    4. Shujun Bi & Le Han & Shaohua Pan, 2013. "Approximation of rank function and its application to the nearest low-rank correlation matrix," Journal of Global Optimization, Springer, vol. 57(4), pages 1113-1137, December.
    5. Sudhanshu K Mishra, 2013. "Global Optimization of Some Difficult Benchmark Functions by Host-Parasite Coevolutionary Algorithm," Economics Bulletin, AccessEcon, vol. 33(1), pages 1-18.
    6. Harry Oviedo, 2023. "Proximal Point Algorithm with Euclidean Distance on the Stiefel Manifold," Mathematics, MDPI, vol. 11(11), pages 1-17, May.
    7. Qingna Li & Houduo Qi & Naihua Xiu, 2011. "Block relaxation and majorization methods for the nearest correlation matrix with factor structure," Computational Optimization and Applications, Springer, vol. 50(2), pages 327-349, October.
    8. Anders Løland & Ragnar Bang Huseby & Nils Lid Hjort & Arnoldo Frigessi, 2013. "Statistical Corrections of Invalid Correlation Matrices," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 807-824, December.
    9. Grubisic, I. & Pietersz, R., 2005. "Efficient Rank Reduction of Correlation Matrices," ERIM Report Series Research in Management ERS-2005-009-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    10. Mishra, SK, 2004. "Optimal solution of the nearest correlation matrix problem by minimization of the maximum norm," MPRA Paper 1783, University Library of Munich, Germany.
    11. Zhu, Xiaojing, 2015. "Computing the nearest low-rank correlation matrix by a simplified SQP algorithm," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 404-414.
    12. Pietersz, R. & van Regenmortel, M., 2005. "Generic Market Models," ERIM Report Series Research in Management ERS-2005-010-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    13. Yulan Liu & Shujun Bi & Shaohua Pan, 2018. "Equivalent Lipschitz surrogates for zero-norm and rank optimization problems," Journal of Global Optimization, Springer, vol. 72(4), pages 679-704, December.
    14. Yitian Qian & Shaohua Pan & Yulan Liu, 2023. "Calmness of partial perturbation to composite rank constraint systems and its applications," Journal of Global Optimization, Springer, vol. 85(4), pages 867-889, April.
    15. Alexander Tchernitser & Dmitri Rubisov, 2009. "Robust estimation of historical volatility and correlations in risk management," Quantitative Finance, Taylor & Francis Journals, vol. 9(1), pages 43-54.
    16. Mishra, SK, 2007. "Completing correlation matrices of arbitrary order by differential evolution method of global optimization: A Fortran program," MPRA Paper 2000, University Library of Munich, Germany.

  27. Heij, C. & Groenen, P.J.F. & van Dijk, D.J.C., 2005. "Forecast comparison of principal component regression and principal covariate regression," Econometric Institute Research Papers EI 2005-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Cornillon, P.-A. & Imam, W. & Matzner-Lober, E., 2008. "Forecasting time series using principal component analysis with respect to instrumental variables," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1269-1280, January.
    2. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
    3. Mestekemper, Thomas & Windmann, Michael & Kauermann, Göran, 2010. "Functional hourly forecasting of water temperature," International Journal of Forecasting, Elsevier, vol. 26(4), pages 684-699, October.
    4. Tsay, Ruey S. & Ando, Tomohiro, 2012. "Bayesian panel data analysis for exploring the impact of subprime financial crisis on the US stock market," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3345-3365.
    5. Peter Exterkate & Dick Van Dijk & Christiaan Heij & Patrick J. F. Groenen, 2013. "Forecasting the Yield Curve in a Data‐Rich Environment Using the Factor‐Augmented Nelson–Siegel Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(3), pages 193-214, April.
    6. Poncela, Pilar & Rodríguez, Julio & Sánchez-Mangas, Rocío & Senra, Eva, 2011. "Forecast combination through dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 27(2), pages 224-237, April.
    7. Guidolin, Massimo & Hyde, Stuart, 2012. "Simple VARs cannot approximate Markov switching asset allocation decisions: An out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3546-3566.
    8. Aguilera, Ana M. & Escabias, Manuel & Valderrama, Mariano J., 2008. "Forecasting binary longitudinal data by a functional PC-ARIMA model," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3187-3197, February.
    9. Simon Lineu Umbach, 2020. "Forecasting with supervised factor models," Empirical Economics, Springer, vol. 58(1), pages 169-190, January.
    10. Heij, C. & Groenen, P.J.F. & van Dijk, D.J.C., 2006. "Time series forecasting by principal covariate regression," Econometric Institute Research Papers EI 2006-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Aguilera, Ana M. & Escabias, Manuel & Valderrama, Mariano J., 2008. "Discussion of different logistic models with functional data. Application to Systemic Lupus Erythematosus," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 151-163, September.

  28. van Deun, K. & Groenen, P.J.F. & Delbeke, L., 2005. "VIPSCAL: A combined vector ideal point model for preference data," Econometric Institute Research Papers EI 2005-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Frank Busing & Mark Rooij, 2009. "Unfolding Incomplete Data: Guidelines for Unfolding Row-Conditional Rank Order Data with Random Missings," Journal of Classification, Springer;The Classification Society, vol. 26(3), pages 329-360, December.

  29. Groenen, P.J.F. & van de Velden, M., 2004. "Multidimensional scaling," Econometric Institute Research Papers EI 2004-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

  30. Groenen, P.J.F. & Giaquinto, P. & Kiers, H.A.L., 2003. "Weighted Majorization Algorithms for Weighted Least Squares Decomposition Models," Econometric Institute Research Papers EI 2003-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. de Leeuw, Jan & Lange, Kenneth, 2009. "Sharp quadratic majorization in one dimension," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2471-2484, May.
    2. de Leeuw, Jan, 2006. "Principal component analysis of binary data by iterated singular value decomposition," Computational Statistics & Data Analysis, Elsevier, vol. 50(1), pages 21-39, January.
    3. Unkel, S. & Trendafilov, N.T., 2010. "A majorization algorithm for simultaneous parameter estimation in robust exploratory factor analysis," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3348-3358, December.

Articles

  1. Ronald de Vlaming & Aysu Okbay & Cornelius A Rietveld & Magnus Johannesson & Patrik K E Magnusson & André G Uitterlinden & Frank J A van Rooij & Albert Hofman & Patrick J F Groenen & A Roy Thurik & Ph, 2017. "Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies," PLOS Genetics, Public Library of Science, vol. 13(1), pages 1-23, January.

    Cited by:

    1. Tabea Schoeler & Jean-Baptiste Pingault & Zoltán Kutalik, 2025. "The impact of self-report inaccuracy in the UK Biobank and its interplay with selective participation," Nature Human Behaviour, Nature, vol. 9(3), pages 584-594, March.
    2. Hans Kippersluis & Pietro Biroli & Rita Dias Pereira & Titus J. Galama & Stephanie Hinke & S. Fleur W. Meddens & Dilnoza Muslimova & Eric A. W. Slob & Ronald Vlaming & Cornelius A. Rietveld, 2023. "Overcoming attenuation bias in regressions using polygenic indices," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Daniel J. Benjamin & David Cesarini & Patrick Turley & Alexander Strudwick Young, 2024. "Social-Science Genomics: Progress, Challenges, and Future Directions," NBER Working Papers 32404, National Bureau of Economic Research, Inc.

  2. Michel Tenenhaus & Arthur Tenenhaus & Patrick J. F. Groenen, 2017. "Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 737-777, September.

    Cited by:

    1. Boyi Guo & Hannah D. Holscher & Loretta S. Auvil & Michael E. Welge & Colleen B. Bushell & Janet A. Novotny & David J. Baer & Nicholas A. Burd & Naiman A. Khan & Ruoqing Zhu, 2023. "Estimating Heterogeneous Treatment Effect on Multivariate Responses Using Random Forests," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(3), pages 545-561, December.
    2. Xiuli Du & Xiaohu Jiang & Jinguan Lin, 2023. "Multinomial Logistic Factor Regression for Multi-source Functional Block-wise Missing Data," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 975-1001, September.
    3. Mohamed Hanafi & Zouhair El Hadri & Abderrahim Sahli & Pasquale Dolce, 2022. "Overcoming convergence problems in PLS path modelling," Computational Statistics, Springer, vol. 37(5), pages 2437-2470, November.
    4. Kudraszow, Nadia L. & Vahnovan, Alejandra V. & Ferrario, Julieta & Fasano, M. Victoria, 2025. "Robust generalized canonical correlation analysis based on scatter matrices," Computational Statistics & Data Analysis, Elsevier, vol. 206(C).
    5. Dybro Liengaard, Benjamin, 2024. "Measurement invariance testing in partial least squares structural equation modeling," Journal of Business Research, Elsevier, vol. 177(C).
    6. Sera Şanlı, 2023. "Untapped potentials on a well‐endowed plate: A sustainable future catalogue for the harmony of renewable technologies with the water‐energy‐climate‐SDGs nexus," Natural Resources Forum, Blackwell Publishing, vol. 47(4), pages 672-698, November.
    7. Pol Castellano-Escuder & Derek K. Zachman & Kevin Han & Matthey D. Hirschey, 2025. "GAUDI: interpretable multi-omics integration with UMAP embeddings and density-based clustering," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
    8. Heungsun Hwang & Gyeongcheol Cho, 2020. "Global Least Squares Path Modeling: A Full-Information Alternative to Partial Least Squares Path Modeling," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 947-972, December.
    9. Anna L. Tyler & J. Matthew Mahoney & Mark P. Keller & Candice N. Baker & Margaret Gaca & Anuj Srivastava & Isabela Gerdes Gyuricza & Madeleine J. Braun & Nadia A. Rosenthal & Alan D. Attie & Gary A. C, 2025. "Transcripts with high distal heritability mediate genetic effects on complex metabolic traits," Nature Communications, Nature, vol. 16(1), pages 1-21, December.

  3. Aysu Okbay & Jonathan P. Beauchamp & Mark Alan Fontana & James J. Lee & Tune H. Pers & Cornelius A. Rietveld & Patrick Turley & Guo-Bo Chen & Valur Emilsson & S. Fleur W. Meddens & Sven Oskarsson & Jo, 2016. "Genome-wide association study identifies 74 loci associated with educational attainment," Nature, Nature, vol. 533(7604), pages 539-542, May.
    See citations under working paper version above.
  4. Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016. "Nonlinear forecasting with many predictors using kernel ridge regression," International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.
    See citations under working paper version above.
  5. Groenen, Patrick J. F. & van de Velden, Michel, 2016. "Multidimensional Scaling by Majorization: A Review," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 73(i08).

    Cited by:

    1. Marc C. Robini & Lihui Wang & Yuemin Zhu, 2024. "The appeals of quadratic majorization–minimization," Journal of Global Optimization, Springer, vol. 89(3), pages 509-558, July.
    2. Eyal Gur & Shoham Sabach & Shimrit Shtern, 2023. "Nested Alternating Minimization with FISTA for Non-convex and Non-smooth Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 199(3), pages 1130-1157, December.

  6. Michael J. Greenacre & Patrick J. F. Groenen, 2016. "Weighted Euclidean Biplots," Journal of Classification, Springer;The Classification Society, vol. 33(3), pages 442-459, October.
    See citations under working paper version above.
  7. Patrick Groenen & Niël Roux & Sugnet Gardner-Lubbe, 2015. "Spline-based nonlinear biplots," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(2), pages 219-238, June.

    Cited by:

    1. Gardner-Lubbe, Sugnet, 2016. "A triplot for multiclass classification visualisation," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 20-32.
    2. Jose Giovany Babativa-Márquez & José Luis Vicente-Villardón, 2021. "Logistic Biplot by Conjugate Gradient Algorithms and Iterated SVD," Mathematics, MDPI, vol. 9(16), pages 1-19, August.
    3. Julio César Hernández-Sánchez & José Luis Vicente-Villardón, 2017. "Logistic biplot for nominal data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 307-326, June.

  8. Pieter Schoonees & Michel Velden & Patrick Groenen, 2015. "Constrained Dual Scaling for Detecting Response Styles in Categorical Data," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 968-994, December.
    See citations under working paper version above.
  9. Matthijs J H M van der Loos & Cornelius A Rietveld & Niina Eklund & Philipp D Koellinger & Fernando Rivadeneira & Gonçalo R Abecasis & Georgina A Ankra-Badu & Sebastian E Baumeister & Daniel J Benjami, 2013. "The Molecular Genetic Architecture of Self-Employment," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.

    Cited by:

    1. A. Roy Thurik & David B. Audretsch & Jörn H. Block & Andrew Burke & Martin A. Carree & Marcus Dejardin & Cornelius A. Rietveld & Mark Sanders & Ute Stephan & Johan Wiklund, 2024. "The impact of entrepreneurship research on other academic fields," Small Business Economics, Springer, vol. 62(2), pages 727-751, February.
    2. Matthew J. Lindquist & Joeri Sol & Mirjam Van Praag, 2015. "Why Do Entrepreneurial Parents Have Entrepreneurial Children?," Journal of Labor Economics, University of Chicago Press, vol. 33(2), pages 269-296.
    3. David B. Audretsch & Martin Obschonka & Samuel D. Gosling & Jeff Potter, 2017. "A new perspective on entrepreneurial regions: linking cultural identity with latent and manifest entrepreneurship," Small Business Economics, Springer, vol. 48(3), pages 681-697, March.
    4. Fisch, Christian & Franken, Ingmar H.A. & Thurik, Roy, 2021. "Are behavioral and electrophysiological measures of impulsivity useful for predicting entrepreneurship?," Journal of Business Venturing Insights, Elsevier, vol. 16(C).
    5. Graciela Kuechle, 2019. "The contribution of behavior genetics to entrepreneurship: An evolutionary perspective," Journal of Evolutionary Economics, Springer, vol. 29(4), pages 1263-1284, September.
    6. E. Zabelina & D. Tsiring & Yu Chestyunina, 2018. "Personal helplessness and self-reliance as predictors of small business development in Russia: pilot study results," International Entrepreneurship and Management Journal, Springer, vol. 14(2), pages 279-293, June.
    7. Ingrid Verheul & Joern Block & Katrin Burmeister-Lamp & Roy Thurik & Henning Tiemeier & Roxana Turturea, 2015. "ADHD-like behavior and entrepreneurial intentions," Post-Print hal-02015731, HAL.
    8. Martin Obschonka & Eva Schmitt-Rodermund & Antonio Terracciano, 2014. "Personality and the Gender Gap in Self-Employment: A Multi-Nation Study," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-11, August.
    9. Nicos Nicolaou & Phillip H. Phan & Ute Stephan, 2021. "The Biological Perspective in Entrepreneurship Research," Entrepreneurship Theory and Practice, , vol. 45(1), pages 3-17, January.
    10. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    11. Ramoglou, Stratos & Gartner, William B. & Tsang, Eric W.K., 2020. "“Who is an entrepreneur?” is (still) the wrong question," Journal of Business Venturing Insights, Elsevier, vol. 13(C).

  10. Peter Exterkate & Dick Van Dijk & Christiaan Heij & Patrick J. F. Groenen, 2013. "Forecasting the Yield Curve in a Data‐Rich Environment Using the Factor‐Augmented Nelson–Siegel Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(3), pages 193-214, April.
    See citations under working paper version above.
  11. Matthijs Loos & Philipp Koellinger & Patrick Groenen & Cornelius Rietveld & Fernando Rivadeneira & Frank Rooij & André Uitterlinden & Albert Hofman & A. Thurik, 2011. "Candidate gene studies and the quest for the entrepreneurial gene," Small Business Economics, Springer, vol. 37(3), pages 269-275, October.

    Cited by:

    1. A. Roy Thurik & David B. Audretsch & Jörn H. Block & Andrew Burke & Martin A. Carree & Marcus Dejardin & Cornelius A. Rietveld & Mark Sanders & Ute Stephan & Johan Wiklund, 2024. "The impact of entrepreneurship research on other academic fields," Small Business Economics, Springer, vol. 62(2), pages 727-751, February.
    2. Matthijs J H M van der Loos & Cornelius A Rietveld & Niina Eklund & Philipp D Koellinger & Fernando Rivadeneira & Gonçalo R Abecasis & Georgina A Ankra-Badu & Sebastian E Baumeister & Daniel J Benjami, 2013. "The Molecular Genetic Architecture of Self-Employment," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    3. Hyytinen, Ari & Ilmakunnas, Pekka & Toivanen, Otto, 2013. "The return-to-entrepreneurship puzzle," Labour Economics, Elsevier, vol. 20(C), pages 57-67.
    4. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    5. Hunt, Richard A. & Lerner, Daniel A. & Ortiz-Hunt, Avery, 2022. "Lassie shrugged: The premise and importance of considering non-human entrepreneurial action," Journal of Business Venturing Insights, Elsevier, vol. 17(C).
    6. Jonathan P. Beauchamp & David Cesarini & Magnus Johannesson & Matthijs J. H. M. van der Loos & Philipp D. Koellinger & Patrick J. F. Groenen & James H. Fowler & J. Niels Rosenquist & A. Roy Thurik & N, 2011. "Molecular Genetics and Economics," Journal of Economic Perspectives, American Economic Association, vol. 25(4), pages 57-82, Fall.

  12. Christiaan Heij & Dick van Dijk & Patrick J.F. Groenen, 2011. "Forecasting with Leading Indicators by means of the Principal Covariate Index," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2011(1), pages 73-92.

    Cited by:

    1. H. Burcu Gurcihan & Gonul Sengul & Arzu Yavuz, 2013. "A Quest for Leading Indicators of the Turkish Unemployment Rate," Working Papers 1341, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.

  13. Jonathan P. Beauchamp & David Cesarini & Magnus Johannesson & Matthijs J. H. M. van der Loos & Philipp D. Koellinger & Patrick J. F. Groenen & James H. Fowler & J. Niels Rosenquist & A. Roy Thurik & N, 2011. "Molecular Genetics and Economics," Journal of Economic Perspectives, American Economic Association, vol. 25(4), pages 57-82, Fall.

    Cited by:

    1. De Neve, Jan-Emmanuel & Fowler, James H., 2014. "Credit card borrowing and the monoamine oxidase A (MAOA) gene," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 428-439.
    2. Erkan Gören, 2015. "The Relationship Between Novelty-Seeking Traits and Comparative Economic Development," Working Papers V-374-15, University of Oldenburg, Department of Economics, revised Jan 2015.
    3. Nicola Barban & Elisabetta De Cao & Sonia Oreffice, 2016. "Assortative Mating on Education: A Genetic Assessment," Economics Series Working Papers 791, University of Oxford, Department of Economics.
    4. Pietro Biroli & Titus Galama & Stephanie von Hinke & Hans van Kippersluis & Kevin Thom, 2022. "Economics and Econometrics of Gene-Environment Interplay," Bristol Economics Discussion Papers 22/759, School of Economics, University of Bristol, UK.
    5. Jan-Emmanuel De Neve & James H. Fowler & Bruno S. Frey, 2010. "Genes, economics, and happiness," IEW - Working Papers 475, Institute for Empirical Research in Economics - University of Zurich.
    6. Navarro Alfredo M., 2023. "Genetics and Economics," Asociación Argentina de Economía Política: Working Papers 4677, Asociación Argentina de Economía Política.
    7. Terhi Maczulskij, 2012. "Employment sector and pay gaps: genetic and environmental influences," ERSA conference papers ersa12p755, European Regional Science Association.
    8. Wei, Xu & Zhou, Yi & Zhou, Yimin, 2022. "Signaling of earlier-born Children's endowments, intra-household allocation, and birth-order effects," Economic Modelling, Elsevier, vol. 108(C).
    9. Matthijs J H M van der Loos & Cornelius A Rietveld & Niina Eklund & Philipp D Koellinger & Fernando Rivadeneira & Gonçalo R Abecasis & Georgina A Ankra-Badu & Sebastian E Baumeister & Daniel J Benjami, 2013. "The Molecular Genetic Architecture of Self-Employment," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    10. Jean-Francois Maystadt & Guiseppe Migali, 2017. "The transmission of health across 7 generations in China, 1789-1906," Working Papers of LICOS - Centre for Institutions and Economic Performance 587013, KU Leuven, Faculty of Economics and Business (FEB), LICOS - Centre for Institutions and Economic Performance.
    11. Brunello, Giorgio & Sanz-de-Galdeano, Anna & Terskaya, Anastasia, 2020. "Not only in my genes: The effects of peers’ genotype on obesity," Journal of Health Economics, Elsevier, vol. 72(C).
    12. Lauren L. Schmitz & Dalton Conley, 2016. "The Effect of Vietnam-Era Conscription and Genetic Potential for Educational Attainment on Schooling Outcomes," NBER Working Papers 22393, National Bureau of Economic Research, Inc.
    13. Camelia M Kuhnen & Gregory R Samanez-Larkin & Brian Knutson, 2013. "Serotonergic Genotypes, Neuroticism, and Financial Choices," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-9, January.
    14. Cronqvist, Henrik & Siegel, Stephan, 2014. "The genetics of investment biases," Journal of Financial Economics, Elsevier, vol. 113(2), pages 215-234.
    15. Jonathan P. Beauchamp & David Cesarini & Magnus Johannesson, 2017. "The psychometric and empirical properties of measures of risk preferences," Journal of Risk and Uncertainty, Springer, vol. 54(3), pages 203-237, June.
    16. Nicholas W. Papageorge & Kevin Thom, 2018. "Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study," Working Papers 2018-076, Human Capital and Economic Opportunity Working Group.
    17. Pereira, Rita & Biroli, Pietro & von hinke, stephanie & Van Kippersluis, Hans & Galama, Titus & Rietveld, Niels & Thom, Kevin, 2022. "Gene-Environment Interplay in the Social Sciences," OSF Preprints d96z3, Center for Open Science.
    18. Owen Thompson, 2017. "Gene–Environment Interaction in the Intergenerational Transmission of Asthma," Health Economics, John Wiley & Sons, Ltd., vol. 26(11), pages 1337-1352, November.
    19. Guiso, Luigi & Sodini, Paolo, 2013. "Household Finance: An Emerging Field," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1397-1532, Elsevier.
    20. Amitabh Chandra & Courtney Coile & Corina Mommaerts, 2020. "What Can Economics Say About Alzheimer's Disease?," NBER Working Papers 27760, National Bureau of Economic Research, Inc.
    21. Stenberg, Anders, 2013. "Interpreting estimates of heritability – A note on the twin decomposition," Economics & Human Biology, Elsevier, vol. 11(2), pages 201-205.
    22. David Cesarini & Magnus Johannesson & Patrik K. E. Magnusson & Björn Wallace, 2012. "The Behavioral Genetics of Behavioral Anomalies," Management Science, INFORMS, vol. 58(1), pages 21-34, January.
    23. Richard Sias & Laura Starks & Harry J. Turtle, 2020. "Molecular Genetics, Risk Aversion, Return Perceptions, and Stock Market Participation," NBER Working Papers 27638, National Bureau of Economic Research, Inc.
    24. Xue, Sen & Kidd, Michael P. & Le, Anh T. & Kirk, Kathy & Martin, Nicholas G., 2019. "The Role of Locus of Control in Education, Occupation, Income and Healthy Habits: Evidence from Australian Twins," GLO Discussion Paper Series 371, Global Labor Organization (GLO).
    25. Jason Collins & Boris Baer & Ernst Juerg Weber, 2016. "Evolutionary Biology in Economics: A Review," The Economic Record, The Economic Society of Australia, vol. 92(297), pages 291-312, June.
    26. Xue, Sen & Kidd, Michael P. & Le, Anh.T. & Kirk, Kathy & Martin, Nicholas G., 2020. "The role of locus of control in adulthood outcomes: Evidence from Australian twins," Journal of Economic Behavior & Organization, Elsevier, vol. 179(C), pages 566-588.
    27. Barban, Nicola & De Cao, Elisabetta & Oreffice, Sonia & Quintana-Domeque, Climent, 2021. "The effect of education on spousal education: A genetic approach," Labour Economics, Elsevier, vol. 71(C).
    28. Gören, Erkan, 2017. "The persistent effects of novelty-seeking traits on comparative economic development," Journal of Development Economics, Elsevier, vol. 126(C), pages 112-126.
    29. Vanessa Mertins & Andrea B. Schote & Jobst Meyer, 2013. "Variants of the Monoamine Oxidase A Gene (MAOA) Predict Free-riding Behavior in Women in a Strategic Public Goods Experiment," IAAEU Discussion Papers 201302, Institute of Labour Law and Industrial Relations in the European Union (IAAEU).
    30. López Ulloa, Beatriz Fabiola & Møller, Valerie & Sousa-Poza, Alfonso, 2013. "How does subjective well-being evolve with age? A literature review," FZID Discussion Papers 72-2013, University of Hohenheim, Center for Research on Innovation and Services (FZID).
    31. Nuñez, Roy, 2020. "Obesity and labor market in Peru," MPRA Paper 105621, University Library of Munich, Germany.
    32. Chew, Soo Hong & Ebstein, Richard P. & Zhong, Songfa, 2013. "Sex-hormone genes and gender difference in ultimatum game: Experimental evidence from China and Israel," Journal of Economic Behavior & Organization, Elsevier, vol. 90(C), pages 28-42.
    33. Björklund, Anders & Jäntti, Markus, 2012. "How important is family background for labor-economic outcomes?," Labour Economics, Elsevier, vol. 19(4), pages 465-474.
    34. Cobb-Clark, Deborah A., 2016. "Biology and Gender in the Labor Market," IZA Discussion Papers 10386, Institute of Labor Economics (IZA).
    35. Yu.G. Myslyakova & E.A. Shamova & N.P. Neklyudova, 2020. "Social and Economic Genotype Territories of the Advancing Development on Example of the Ural Region," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 19(3), pages 310-328.
    36. Cardella, Eric & Kalcheva, Ivalina & Shang, Danjue, 2018. "Financial markets and genetic variation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 64-89.
    37. Sezen GÜNGÖR, 2019. "Genes Involved in both Dopaminergic and Serotonergic Pathways and Financial Decision Making," Prizren Social Science Journal, SHIKS, vol. 3(2), pages 21-26, August.
    38. Peter A.G. van Bergeijk, 2019. "Deglobalization 2.0," Books, Edward Elgar Publishing, number 18560.

  14. Heij, Christiaan & van Dijk, Dick & Groenen, Patrick J.F., 2011. "Real-time macroeconomic forecasting with leading indicators: An empirical comparison," International Journal of Forecasting, Elsevier, vol. 27(2), pages 466-481, April.

    Cited by:

    1. Knut Lehre Seip & Yunus Yilmaz & Michael Schröder, 2019. "Comparing Sentiment- and Behavioral-Based Leading Indexes for Industrial Production: When Does Each Fail?," Economies, MDPI, vol. 7(4), pages 1-18, October.
    2. Lise Pichette & Marie-Noëlle Robitaille, 2017. "Assessing the Business Outlook Survey Indicator Using Real-Time Data," Discussion Papers 17-5, Bank of Canada.
    3. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    4. Galdi, Giulio & Casarin, Roberto & Ferrari, Davide & Fezzi, Carlo & Ravazzolo, Francesco, 2023. "Nowcasting industrial production using linear and non-linear models of electricity demand," Energy Economics, Elsevier, vol. 126(C).
    5. Philip Hans Franses & Eva Janssens, 2019. "Spurious principal components," Applied Economics Letters, Taylor & Francis Journals, vol. 26(1), pages 37-39, January.
    6. Guo, Jin & Wen, Xiaoqian, 2024. "Option listing and underlying commodity futures volatility in China," Economic Modelling, Elsevier, vol. 141(C).
    7. Sarula Bai & Jaewon Jung & Shun Li, 2024. "The Spillover Effects of Market Sentiments on Global Stock Market Volatility: A Multi-Country GJR-GARCH-MIDAS Approach," JRFM, MDPI, vol. 17(12), pages 1-23, December.
    8. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2012. "Evaluating Macroeconomic Forecasts: A Concise Review of Some Recent Developments," Documentos de Trabajo del ICAE 2012-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    9. Jianhao Lin & Jiacheng Fan & Yifan Zhang & Liangyuan Chen, 2023. "Real‐time macroeconomic projection using narrative central bank communication," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 202-221, March.
    10. Soh, Ann-Ni, 2020. "A Review on the Leading Indicator Approach towards Economic Forecasting," MPRA Paper 103854, University Library of Munich, Germany.
    11. Roberto Golinelli & Giuseppe Parigi, 2013. "Tracking world trade and GDP in real time," Temi di discussione (Economic working papers) 920, Bank of Italy, Economic Research and International Relations Area.
    12. Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Working Papers 317, Bank of Greece.
    13. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," Research Technical Papers 07/RT/12, Central Bank of Ireland.

  15. Philipp Koellinger & Matthijs Loos & Patrick Groenen & A. Thurik & Fernando Rivadeneira & Frank Rooij & André Uitterlinden & Albert Hofman, 2010. "Genome-wide association studies in economics and entrepreneurship research: promises and limitations," Small Business Economics, Springer, vol. 35(1), pages 1-18, July.

    Cited by:

    1. A. Roy Thurik & David B. Audretsch & Jörn H. Block & Andrew Burke & Martin A. Carree & Marcus Dejardin & Cornelius A. Rietveld & Mark Sanders & Ute Stephan & Johan Wiklund, 2024. "The impact of entrepreneurship research on other academic fields," Small Business Economics, Springer, vol. 62(2), pages 727-751, February.
    2. Matthijs J H M van der Loos & Cornelius A Rietveld & Niina Eklund & Philipp D Koellinger & Fernando Rivadeneira & Gonçalo R Abecasis & Georgina A Ankra-Badu & Sebastian E Baumeister & Daniel J Benjami, 2013. "The Molecular Genetic Architecture of Self-Employment," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    3. Matthew J. Lindquist & Joeri Sol & Mirjam Van Praag, 2015. "Why Do Entrepreneurial Parents Have Entrepreneurial Children?," Journal of Labor Economics, University of Chicago Press, vol. 33(2), pages 269-296.
    4. Maha Aly & David B. Audretsch & Heike Grimm, 2021. "Emotional skills for entrepreneurial success: the promise of entrepreneurship education and policy," The Journal of Technology Transfer, Springer, vol. 46(5), pages 1611-1629, October.
    5. Matthijs Loos & Philipp Koellinger & Patrick Groenen & Cornelius Rietveld & Fernando Rivadeneira & Frank Rooij & André Uitterlinden & Albert Hofman & A. Thurik, 2011. "Candidate gene studies and the quest for the entrepreneurial gene," Small Business Economics, Springer, vol. 37(3), pages 269-275, October.
    6. Fisch, Christian & Franken, Ingmar H.A. & Thurik, Roy, 2021. "Are behavioral and electrophysiological measures of impulsivity useful for predicting entrepreneurship?," Journal of Business Venturing Insights, Elsevier, vol. 16(C).
    7. Giuseppe Criaco & Philipp Sieger & Karl Wennberg & Francesco Chirico & Tommaso Minola, 2017. "Parents’ performance in entrepreneurship as a “double-edged sword” for the intergenerational transmission of entrepreneurship," Small Business Economics, Springer, vol. 49(4), pages 841-864, December.
    8. Singer Burton, 2011. "Genome-Phenome Linkages in Human Population Surveys, with Special Emphasis on the Health and Retirement Survey," Forum for Health Economics & Policy, De Gruyter, vol. 14(2), pages 1-24, April.
    9. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    10. Antonio Dottore & Suleiman K. Kassicieh, 2017. "Predicting Future Technopreneurs Among Inventors," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 1-24, June.
    11. Lerner, Daniel A. & Hatak, Isabella & Rauch, Andreas, 2018. "Deep roots? Behavioral Inhibition and Behavioral Activation System (BIS/BAS) sensitivity and entrepreneurship," Journal of Business Venturing Insights, Elsevier, vol. 9(C), pages 107-115.
    12. Zoltan Acs & Emma Lappi, 2021. "Entrepreneurship, culture, and the epigenetic revolution: a research note," Small Business Economics, Springer, vol. 56(4), pages 1287-1307, April.
    13. Hunt, Richard A. & Lerner, Daniel A. & Ortiz-Hunt, Avery, 2022. "Lassie shrugged: The premise and importance of considering non-human entrepreneurial action," Journal of Business Venturing Insights, Elsevier, vol. 17(C).

  16. Blasius, J. & Greenacre, M. & Groenen, P.J.F. & van de Velden, M., 2009. "Special issue on correspondence analysis and related methods," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3103-3106, June.

    Cited by:

    1. Kenneth David Strang, 2012. "Man versus math: Behaviorist exploration of post-crisis non-banking asset management," Journal of Asset Management, Palgrave Macmillan, vol. 13(5), pages 348-367, October.
    2. K. Fernández-Aguirre & M. Garín-Martín & J. Modroño-Herrán, 2014. "Visual displays: analytical study and applications to graphs and real data," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 2209-2224, July.

  17. van de Velden, Michel & Groenen, Patrick J.F. & Poblome, Jeroen, 2009. "Seriation by constrained correspondence analysis: A simulation study," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3129-3138, June.
    See citations under working paper version above.
  18. Joost Rosmalen & Patrick Groenen & Javier Trejos & William Castillo, 2009. "Optimization Strategies for Two-Mode Partitioning," Journal of Classification, Springer;The Classification Society, vol. 26(2), pages 155-181, August.

    Cited by:

    1. Jan Schepers & Hans-Hermann Bock & Iven Mechelen, 2017. "Maximal Interaction Two-Mode Clustering," Journal of Classification, Springer;The Classification Society, vol. 34(1), pages 49-75, April.
    2. J. Vera & Rodrigo Macías & Willem Heiser, 2013. "Cluster Differences Unfolding for Two-Way Two-Mode Preference Rating Data," Journal of Classification, Springer;The Classification Society, vol. 30(3), pages 370-396, October.
    3. Stephen L. France & Wen Chen & Yumin Deng, 2017. "ADCLUS and INDCLUS: analysis, experimentation, and meta-heuristic algorithm extensions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 371-393, June.
    4. Michael Brusco & Douglas Steinley, 2011. "A Tabu-Search Heuristic for Deterministic Two-Mode Blockmodeling of Binary Network Matrices," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 612-633, October.
    5. van Dijk, A. & van Rosmalen, J.M. & Paap, R., 2009. "A Bayesian approach to two-mode clustering," Econometric Institute Research Papers EI 2009-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Brusco, Michael J., 2014. "A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 38-53.
    7. Michael Brusco & Patrick Doreian, 2015. "An Exact Algorithm for the Two-Mode KL-Means Partitioning Problem," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 481-515, October.
    8. Paolo Giordani & Henk Kiers, 2012. "FINDCLUS: Fuzzy INdividual Differences CLUStering," Journal of Classification, Springer;The Classification Society, vol. 29(2), pages 170-198, July.
    9. Jan Schepers & Iven Mechelen & Eva Ceulemans, 2011. "The Real-Valued Model of Hierarchical Classes," Journal of Classification, Springer;The Classification Society, vol. 28(3), pages 363-389, October.

  19. Heij, Christiaan & van Dijk, Dick & Groenen, Patrick J.F., 2008. "Macroeconomic forecasting with matched principal components," International Journal of Forecasting, Elsevier, vol. 24(1), pages 87-100.

    Cited by:

    1. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
    2. Philip Hans Franses & Rianne Legerstee, 2010. "A Unifying View On Multi‐Step Forecasting Using An Autoregression," Journal of Economic Surveys, Wiley Blackwell, vol. 24(3), pages 389-401, July.
    3. Guidolin, Massimo & Hyde, Stuart, 2012. "Simple VARs cannot approximate Markov switching asset allocation decisions: An out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3546-3566.
    4. Richard G. Anderson & Jane M. Binner & Björn Hagströmer & Birger Nilsson, 2009. "Dynamics in systematic liquidity," Working Papers 2009-025, Federal Reserve Bank of St. Louis.
    5. Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Working Papers 317, Bank of Greece.
    6. Guidolin, Massimo & Hyde, Stuart, 2012. "Can VAR models capture regime shifts in asset returns? A long-horizon strategic asset allocation perspective," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 695-716.

  20. Heij, Christiaan & Groenen, Patrick J.F. & van Dijk, Dick, 2007. "Forecast comparison of principal component regression and principal covariate regression," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3612-3625, April.
    See citations under working paper version above.
  21. Geweke, John & Groenen, Patrick J.F. & Paap, Richard & van Dijk, Herman K., 2007. "Computational techniques for applied econometric analysis of macroeconomic and financial processes," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3506-3508, April.

    Cited by:

    1. Wolfgang Polasek, 2008. "Jean-Michel Marin, Christian P. Robert: Bayesian Core. A Practical Approach to Computational Bayesian Statistics," Statistical Papers, Springer, vol. 49(2), pages 397-398, April.

  22. Patrick J. F. Groenen & L. Andries van der Ark, 2006. "Visions of 70 years of psychometrics: the past, present, and future," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(2), pages 135-144, May.

    Cited by:

    1. Lisa D. Wijsen & Denny Borsboom, 2021. "Perspectives on Psychometrics Interviews with 20 Past Psychometric Society Presidents," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 327-343, March.
    2. Lisa D. Wijsen & Denny Borsboom & Tiago Cabaço & Willem J. Heiser, 2019. "An Academic Genealogy of Psychometric Society Presidents," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 562-588, June.

  23. Groenen, P.J.F. & Winsberg, S. & Rodriguez, O. & Diday, E., 2006. "I-Scal: Multidimensional scaling of interval dissimilarities," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 360-378, November.

    Cited by:

    1. Eufr�sio de A. Lima Neto & Ulisses U. dos Anjos, 2015. "Regression model for interval-valued variables based on copulas," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(9), pages 2010-2029, September.
    2. Groenen, P.J.F. & Terada, Y., 2015. "Symbolic Multidimensional Scaling," Econometric Institute Research Papers EI 2015-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Dehnel Grażyna & Walesiak Marek, 2019. "A Comparative Analysis Of Economic Efficiency Of Medium-Sized Manufacturing Enterprises In Districts Of Wielkopolska Province Using The Hybrid Approach With Metric And Interval-Valued Data," Statistics in Transition New Series, Statistics Poland, vol. 20(2), pages 49-67, June.
    4. Pełka Marcin, 2019. "Analysis of Happiness in EU Countries Using the Multi-Model Classification based on Models of Symbolic Data," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(3), pages 15-25, September.
    5. Pełka Marcin, 2019. "Assessment of the Development of the European Oecd Countries with the Application of Linear Ordering and Ensemble Clustering of Symbolic Data," Folia Oeconomica Stetinensia, Sciendo, vol. 19(2), pages 117-133, December.
    6. Maia, André Luis Santiago & de Carvalho, Francisco de A.T., 2011. "Holt’s exponential smoothing and neural network models for forecasting interval-valued time series," International Journal of Forecasting, Elsevier, vol. 27(3), pages 740-759.
    7. Lima Neto, Eufrásio de A. & de Carvalho, Francisco de A.T., 2010. "Constrained linear regression models for symbolic interval-valued variables," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 333-347, February.
    8. Coppi, Renato & Gil, Maria A. & Kiers, Henk A.L., 2006. "The fuzzy approach to statistical analysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 1-14, November.
    9. Groenen, P.J.F. & Winsberg, S., 2006. "3WaySym-Scal: three-way symbolic multidimensional scaling," Econometric Institute Research Papers EI 2006-49, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Zaborski Artur & Pełka Marcin, 2023. "The Unfolding Analysis for Symbolic Objects Based on the Example of the External Car Advertisement Evaluation," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 27(4), pages 15-28, December.
    11. Maia, André Luis Santiago & de Carvalho, Francisco de A.T., 2011. "Holt's exponential smoothing and neural network models for forecasting interval-valued time series," International Journal of Forecasting, Elsevier, vol. 27(3), pages 740-759, July.
    12. Groenen, P.J.F. & Borg, I., 2013. "The Past, Present, and Future of Multidimensional Scaling," Econometric Institute Research Papers EI 2013-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  24. K. Deun & P. Groenen & W. Heiser & F. Busing & L. Delbeke, 2005. "Interpreting degenerate solutions in unfolding by use of the vector model and the compensatory distance model," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 45-69, March.

    Cited by:

    1. Joonwook Park & Wayne DeSarbo & John Liechty, 2008. "A Hierarchical Bayesian Multidimensional Scaling Methodology for Accommodating Both Structural and Preference Heterogeneity," Psychometrika, Springer;The Psychometric Society, vol. 73(3), pages 451-472, September.
    2. Selin Atalay & Wayne S. Desarbo & Simon J. Blanchard, 2009. "A three-way clusterwise multidimensional unfolding procedure for the spatial representation of context dependent preferences," Post-Print hal-00458377, HAL.
    3. Willem Heiser, 2004. "Geometric representation of association between categories," Psychometrika, Springer;The Psychometric Society, vol. 69(4), pages 513-545, December.
    4. Vera, J. Fernando & Macas, Rodrigo & Heiser, Willem J., 2009. "A dual latent class unfolding model for two-way two-mode preference rating data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3231-3244, June.
    5. Marta Nai Ruscone & Daniel Fernández & Antonio D’Ambrosio, 2024. "Copula-Based Non-Metric Unfolding on Augmented Data Matrix," Journal of Classification, Springer;The Classification Society, vol. 41(3), pages 678-697, November.
    6. K. Van Deun & P. J. F. Groenen, 2005. "Majorization Algorithms for Inspecting Circles, Ellipses, Squares, Rectangles, and Rhombi," Operations Research, INFORMS, vol. 53(6), pages 957-967, December.

  25. Frank Busing & Patrick Groenen & Willem Heiser, 2005. "Avoiding degeneracy in multidimensional unfolding by penalizing on the coefficient of variation," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 71-98, March.

    Cited by:

    1. Chen, Yunxiao & Ying, Zhiliang & Zhang, Haoran, 2021. "Unfolding-model-based visualization: theory, method and applications," LSE Research Online Documents on Economics 108876, London School of Economics and Political Science, LSE Library.
    2. Khanh Duong, 2024. "Is meritocracy just? New evidence from Boolean analysis and Machine learning," Journal of Computational Social Science, Springer, vol. 7(2), pages 1795-1821, October.
    3. Joonwook Park & Wayne DeSarbo & John Liechty, 2008. "A Hierarchical Bayesian Multidimensional Scaling Methodology for Accommodating Both Structural and Preference Heterogeneity," Psychometrika, Springer;The Psychometric Society, vol. 73(3), pages 451-472, September.
    4. van de Velden, M. & de Beuckelaer, A. & Groenen, P.J.F. & Busing, F.M.T.A., 2011. "Nonmetric Unfolding of Marketing Data: Degeneracy and Stability," ERIM Report Series Research in Management ERS-2011-006-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Joonwook Park & Priyali Rajagopal & Wayne DeSarbo, 2012. "A New Heterogeneous Multidimensional Unfolding Procedure," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 263-287, April.
    6. Gregory Bonn & Romin Tafarodi, 2013. "Visualizing the Good Life: A Cross-Cultural Analysis," Journal of Happiness Studies, Springer, vol. 14(6), pages 1839-1856, December.
    7. Alessio Baldassarre & Elise Dusseldorp & Antonio D’Ambrosio & Mark de Rooij & Claudio Conversano, 2023. "The Bradley–Terry Regression Trunk approach for Modeling Preference Data with Small Trees," Psychometrika, Springer;The Psychometric Society, vol. 88(4), pages 1443-1465, December.
    8. Antonio D’Ambrosio & Carmela Iorio & Michele Staiano & Roberta Siciliano, 2019. "Median constrained bucket order rank aggregation," Computational Statistics, Springer, vol. 34(2), pages 787-802, June.
    9. Li, Xiangping & Li, Xiang (Robert) & Hudson, Simon, 2013. "The application of generational theory to tourism consumer behavior: An American perspective," Tourism Management, Elsevier, vol. 37(C), pages 147-164.
    10. Selin Atalay & Wayne S. Desarbo & Simon J. Blanchard, 2009. "A three-way clusterwise multidimensional unfolding procedure for the spatial representation of context dependent preferences," Post-Print hal-00458377, HAL.
    11. Samoggia, Antonella & Arvola, Anne & Bertazzoli, Aldo & Gurinovic, Mirjana & Hendrixson, Vaiva & Rivarolifi, Sergio & Ruggeri, Arianna, 2014. "Offering Low-Cost Healthy Food: an Exploration of Food Manufacturers’ and Retailers’ Perspectives," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 17(4), pages 1-32, November.
    12. J. Vera & Rodrigo Macías & Willem Heiser, 2013. "Cluster Differences Unfolding for Two-Way Two-Mode Preference Rating Data," Journal of Classification, Springer;The Classification Society, vol. 30(3), pages 370-396, October.
    13. Khoja, Layla & Chipulu, Maxwell & Jayasekera, Ranadeva, 2019. "Analysis of financial distress cross countries: Using macroeconomic, industrial indicators and accounting data," International Review of Financial Analysis, Elsevier, vol. 66(C).
    14. Junggi Yang & Ungu Kang & Youngho Lee, 2016. "Clinical decision support system in medical knowledge literature review," Information Technology and Management, Springer, vol. 17(1), pages 5-14, March.
    15. Chang Liu & Zhanyu Zhang & Shuya Liu & Qiaoyuan Liu & Baoping Feng & Julia Tanzer, 2019. "Evaluating Agricultural Sustainability Based on the Water–Energy–Food Nexus in the Chenmengquan Irrigation District of China," Sustainability, MDPI, vol. 11(19), pages 1-16, September.
    16. Willem Heiser, 2004. "Geometric representation of association between categories," Psychometrika, Springer;The Psychometric Society, vol. 69(4), pages 513-545, December.
    17. Wayne DeSarbo & Joonwook Park & Crystal Scott, 2008. "A Model-Based Approach for Visualizing the Dimensional Structure of Ordered Successive Categories Preference Data," Psychometrika, Springer;The Psychometric Society, vol. 73(1), pages 1-20, March.
    18. Vera, J. Fernando & Macas, Rodrigo & Heiser, Willem J., 2009. "A dual latent class unfolding model for two-way two-mode preference rating data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3231-3244, June.
    19. Giuseppe Bove & Akinori Okada, 2018. "Methods for the analysis of asymmetric pairwise relationships," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 5-31, March.
    20. Wayne DeSarbo & Joonwook Park & Vithala Rao, 2011. "Deriving joint space positioning maps from consumer preference ratings," Marketing Letters, Springer, vol. 22(1), pages 1-14, March.
    21. Wilde, Pieter de & Junk, Wiebke Marie & Palmtag, Tabea, 2016. "Accountability and opposition to globalization in international assemblies," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 22(4), pages 823-846.
    22. Frank Busing & Mark Rooij, 2009. "Unfolding Incomplete Data: Guidelines for Unfolding Row-Conditional Rank Order Data with Random Missings," Journal of Classification, Springer;The Classification Society, vol. 26(3), pages 329-360, December.
    23. Marta Nai Ruscone & Daniel Fernández & Antonio D’Ambrosio, 2024. "Copula-Based Non-Metric Unfolding on Augmented Data Matrix," Journal of Classification, Springer;The Classification Society, vol. 41(3), pages 678-697, November.
    24. Layla Khoja & Maxwell Chipulu & Ranadeva Jayasekera, 2016. "Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling," Review of Quantitative Finance and Accounting, Springer, vol. 46(3), pages 483-518, April.
    25. Ho, Ying & Chung, Yuho & Lau, Kin-nam, 2010. "Unfolding large-scale marketing data," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 119-132.
    26. Antonio D’Ambrosio & Willem J. Heiser, 2016. "A Recursive Partitioning Method for the Prediction of Preference Rankings Based Upon Kemeny Distances," Psychometrika, Springer;The Psychometric Society, vol. 81(3), pages 774-794, September.
    27. Marti Sagarra & Frank M. T. A. Busing & Cecilio Mar-Molinero & Josep Rialp, 2018. "Assessing the asymmetric effects on branch rivalry of Spanish financial sector restructuring," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 131-153, March.

  26. Raoul Pietersz & Patrick Groenen, 2004. "Rank reduction of correlation matrices by majorization," Quantitative Finance, Taylor & Francis Journals, vol. 4(6), pages 649-662.
    See citations under working paper version above.
  27. Patrick Groenen & Bart-Jan Os & Jacqueline Meulman, 2000. "Optimal scaling by alternating length-constrained nonnegative least squares, with application to distance-based analysis," Psychometrika, Springer;The Psychometric Society, vol. 65(4), pages 511-524, December.

    Cited by:

    1. Jacqueline Meulman, 2003. "Prediction and classification in nonlinear data analysis: Something old, something new, something borrowed, something blue," Psychometrika, Springer;The Psychometric Society, vol. 68(4), pages 493-517, December.
    2. Groenen, P.J.F. & van der Lans, A., 2006. "Multidimensional Scaling with Regional Restrictions for Facet Theory: An Application to Levi's Political Protest Data," ERIM Report Series Research in Management ERS-2006-057-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. van Deun, K. & Groenen, P.J.F. & Delbeke, L., 2005. "VIPSCAL: A combined vector ideal point model for preference data," Econometric Institute Research Papers EI 2005-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. K. Van Deun & P. J. F. Groenen, 2005. "Majorization Algorithms for Inspecting Circles, Ellipses, Squares, Rectangles, and Rhombi," Operations Research, INFORMS, vol. 53(6), pages 957-967, December.

  28. Groenen, Patrick J. F. & Franses, Philip Hans, 2000. "Visualizing time-varying correlations across stock markets," Journal of Empirical Finance, Elsevier, vol. 7(2), pages 155-172, August.

    Cited by:

    1. Chun-Xiao Nie, 2021. "Studying the correlation structure based on market geometry," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 411-441, April.
    2. Carrizosa, Emilio & Guerrero, Vanesa & Romero Morales, Dolores, 2019. "Visualization of complex dynamic datasets by means of mathematical optimization," Omega, Elsevier, vol. 86(C), pages 125-136.
    3. Giampaolo Gabbi, 2005. "Semi-correlations as a tool for geographical and sector asset allocation," The European Journal of Finance, Taylor & Francis Journals, vol. 11(3), pages 271-281.
    4. Bera, Anil K. & Kim, Sangwhan, 2002. "Testing constancy of correlation and other specifications of the BGARCH model with an application to international equity returns," Journal of Empirical Finance, Elsevier, vol. 9(2), pages 171-195, March.
    5. Andrea Beltratti & Claudio Morana, 2006. "Comovements in International Stock Markets," ICER Working Papers 3-2006, ICER - International Centre for Economic Research.
    6. Ji, Aiwen & Shang, Pengjian, 2019. "Analysis of financial time series through forbidden patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    7. Natividad Blasco & Pilar Corredor & Sandra Ferreruela, 2009. "Detecting intentional herding: what lies beneath intraday data in the spanish stock market," Documentos de Trabajo dt2009-01, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    8. Miroslav Plasil & Ivana Kubicova, 2012. "Contingent Claims Analysis And The Inter-Sector Transmission Of Credit Risk," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2011/2012, chapter 0, pages 129-139, Czech National Bank, Research and Statistics Department.
    9. Lehkonen, Heikki & Heimonen, Kari, 2014. "Timescale-dependent stock market comovement: BRICs vs. developed markets," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 90-103.
    10. Wan, Li & Han, Liyan & Xu, Yang & Matousek, Roman, 2021. "Dynamic linkage between the Chinese and global stock markets: A normal mixture approach," Emerging Markets Review, Elsevier, vol. 49(C).
    11. Claudio Morana, 2008. "International stock markets comovements: the role of economic and financial integration," Empirical Economics, Springer, vol. 35(2), pages 333-359, September.
    12. Dirk Brounen & Maarten Jennen, 2009. "Asymmetric Properties of Office Rent Adjustment," The Journal of Real Estate Finance and Economics, Springer, vol. 39(3), pages 336-358, October.

  29. Jacques Commandeur & Patrick Groenen & Jacqueline Meulman, 1999. "A distance-based variety of nonlinear multivariate data analysis, including weights for objects and variables," Psychometrika, Springer;The Psychometric Society, vol. 64(2), pages 169-186, June.

    Cited by:

    1. Beibei Yuan & Willem Heiser & Mark Rooij, 2019. "The δ-Machine: Classification Based on Distances Towards Prototypes," Journal of Classification, Springer;The Classification Society, vol. 36(3), pages 442-470, October.

  30. P. J. F. Groenen & W. J. Heiser & J. J. Meulman, 1999. "Global Optimization in Least-Squares Multidimensional Scaling by Distance Smoothing," Journal of Classification, Springer;The Classification Society, vol. 16(2), pages 225-254, July.

    Cited by:

    1. Michael Brusco & Stephanie Stahl, 2005. "Optimal Least-Squares Unidimensional Scaling: Improved Branch-and-Bound Procedures and Comparison to Dynamic Programming," Psychometrika, Springer;The Psychometric Society, vol. 70(2), pages 253-270, June.
    2. Julius Žilinskas, 2012. "Parallel branch and bound for multidimensional scaling with city-block distances," Journal of Global Optimization, Springer, vol. 54(2), pages 261-274, October.
    3. Groenen, P.J.F. & van de Velden, M., 2004. "Multidimensional scaling," Econometric Institute Research Papers EI 2004-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Groenen, Patrick J. F. & Franses, Philip Hans, 2000. "Visualizing time-varying correlations across stock markets," Journal of Empirical Finance, Elsevier, vol. 7(2), pages 155-172, August.
    5. K. Deun & P. Groenen & W. Heiser & F. Busing & L. Delbeke, 2005. "Interpreting degenerate solutions in unfolding by use of the vector model and the compensatory distance model," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 45-69, March.
    6. Michael Brusco & Hans-Friedrich Köhn & Stephanie Stahl, 2008. "Heuristic Implementation of Dynamic Programming for Matrix Permutation Problems in Combinatorial Data Analysis," Psychometrika, Springer;The Psychometric Society, vol. 73(3), pages 503-522, September.
    7. Dorit S. Hochbaum & Erick Moreno-Centeno & Phillip Yelland & Rodolfo A. Catena, 2011. "Rating Customers According to Their Promptness to Adopt New Products," Operations Research, INFORMS, vol. 59(5), pages 1171-1183, October.
    8. Groenen, P.J.F. & Kaymak, U. & van Rosmalen, J.M., 2006. "Fuzzy clustering with Minkowski distance," Econometric Institute Research Papers EI 2006-24, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Antanas Žilinskas & Julius Žilinskas, 2008. "A hybrid method for multidimensional scaling using city-block distances," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 68(3), pages 429-443, December.
    10. K. Van Deun & P. J. F. Groenen, 2005. "Majorization Algorithms for Inspecting Circles, Ellipses, Squares, Rectangles, and Rhombi," Operations Research, INFORMS, vol. 53(6), pages 957-967, December.
    11. Groenen, P.J.F. & Winsberg, S. & Rodriguez, O. & Diday, E., 2006. "I-Scal: Multidimensional scaling of interval dissimilarities," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 360-378, November.

  31. Willem Heiser & Patrick Groenen, 1997. "Cluster differences scaling with a within-clusters loss component and a fuzzy successive approximation strategy to avoid local minima," Psychometrika, Springer;The Psychometric Society, vol. 62(1), pages 63-83, March.

    Cited by:

    1. van Rosmalen, J.M. & Groenen, P.J.F. & Trejos, J. & Castilli, W., 2005. "Global Optimization strategies for two-mode clustering," Econometric Institute Research Papers EI 2005-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Vichi, Maurizio & Saporta, Gilbert, 2009. "Clustering and disjoint principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3194-3208, June.
    3. J. Fernando Vera & Rodrigo Macías, 2021. "On the Behaviour of K-Means Clustering of a Dissimilarity Matrix by Means of Full Multidimensional Scaling," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 489-513, June.
    4. Elizabeth Ann Maharaj & Pierpaolo D’Urso & Don Galagedera, 2010. "Wavelet-based Fuzzy Clustering of Time Series," Journal of Classification, Springer;The Classification Society, vol. 27(2), pages 231-275, September.
    5. Renato Coppi & Pierpaolo D’Urso & Paolo Giordani, 2010. "A Fuzzy Clustering Model for Multivariate Spatial Time Series," Journal of Classification, Springer;The Classification Society, vol. 27(1), pages 54-88, March.
    6. Renato Coppi & Pierpaolo D'Urso, 2002. "Fuzzy K-means clustering models for triangular fuzzy time trajectories," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(1), pages 21-40, February.
    7. J. Fernando Vera & Ricardo Subiabre & Rodrigo Macías, 2025. "Clustering and Geodesic Scaling of Dissimilarities on the Spherical Surface," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 30(1), pages 172-192, March.
    8. Van Mechelen, Iven & Schepers, Jan, 2007. "A unifying model involving a categorical and/or dimensional reduction for multimode data," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 537-549, September.
    9. Pierpaolo D’Urso & Livia Giovanni & Riccardo Massari, 2015. "Trimmed fuzzy clustering for interval-valued data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(1), pages 21-40, March.
    10. Patrick Groenen & Willem Heiser, 1996. "The tunneling method for global optimization in multidimensional scaling," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 529-550, September.
    11. Selin Atalay & Wayne S. Desarbo & Simon J. Blanchard, 2009. "A three-way clusterwise multidimensional unfolding procedure for the spatial representation of context dependent preferences," Post-Print hal-00458377, HAL.
    12. Joost Rosmalen & Patrick Groenen & Javier Trejos & William Castillo, 2009. "Optimization Strategies for Two-Mode Partitioning," Journal of Classification, Springer;The Classification Society, vol. 26(2), pages 155-181, August.
    13. Heungsun Hwang & Wayne Desarbo & Yoshio Takane, 2007. "Fuzzy Clusterwise Generalized Structured Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 181-198, June.
    14. J. Vera & Rodrigo Macías & Willem Heiser, 2013. "Cluster Differences Unfolding for Two-Way Two-Mode Preference Rating Data," Journal of Classification, Springer;The Classification Society, vol. 30(3), pages 370-396, October.
    15. Pierpaolo D’Urso & Leonardo Salvatore Alaimo & Livia Giovanni & Riccardo Massari, 2022. "Well-Being in the Italian Regions Over Time," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 599-627, June.
    16. Vera, J. Fernando & Macas, Rodrigo & Heiser, Willem J., 2009. "A dual latent class unfolding model for two-way two-mode preference rating data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3231-3244, June.
    17. Tianyu Tan & Hye Suk & Heungsun Hwang & Jooseop Lim, 2013. "Functional fuzzy clusterwise regression analysis," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 7(1), pages 57-82, March.
    18. Pierpaolo D’Urso & Livia De Giovanni & Riccardo Massari & Francesca G. M. Sica, 2019. "Cross Sectional and Longitudinal Fuzzy Clustering of the NUTS and Positioning of the Italian Regions with Respect to the Regional Competitiveness Index (RCI) Indicators with Contiguity Constraints," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(3), pages 609-650, December.
    19. B. Lafuente-Rego & P. D’Urso & J. A. Vilar, 2020. "Robust fuzzy clustering based on quantile autocovariances," Statistical Papers, Springer, vol. 61(6), pages 2393-2448, December.
    20. C Mar-Molinero & J Mingers, 2007. "An evaluation of the limitations of, and alternatives to, the Co-Plot methodology," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(7), pages 874-886, July.
    21. Frank Busing & Mark Rooij, 2009. "Unfolding Incomplete Data: Guidelines for Unfolding Row-Conditional Rank Order Data with Random Missings," Journal of Classification, Springer;The Classification Society, vol. 26(3), pages 329-360, December.
    22. Pierpaolo D’Urso & Livia Giovanni & Riccardo Massari & Dario Lallo, 2013. "Noise fuzzy clustering of time series by autoregressive metric," METRON, Springer;Sapienza Università di Roma, vol. 71(3), pages 217-243, November.
    23. D’Urso, Pierpaolo & Manca, Germana & Waters, Nigel & Girone, Stefania, 2019. "Visualizing regional clusters of Sardinia's EU supported agriculture: A Spatial Fuzzy Partitioning Around Medoids," Land Use Policy, Elsevier, vol. 83(C), pages 571-580.
    24. Marta Nai Ruscone & Daniel Fernández & Antonio D’Ambrosio, 2024. "Copula-Based Non-Metric Unfolding on Augmented Data Matrix," Journal of Classification, Springer;The Classification Society, vol. 41(3), pages 678-697, November.
    25. Coppi, Renato & D'Urso, Pierpaolo, 2003. "Three-way fuzzy clustering models for LR fuzzy time trajectories," Computational Statistics & Data Analysis, Elsevier, vol. 43(2), pages 149-177, June.
    26. Pierpaolo D'Urso & Girish Prayag & Marta Disegna & Riccardo Massari, 2013. "Market Segmentation using Bagged Fuzzy C–Means (BFCM): Destination Image of Western Europe among Chinese Travellers," BEMPS - Bozen Economics & Management Paper Series BEMPS13, Faculty of Economics and Management at the Free University of Bozen.
    27. J. Vera & Rodrigo Macías & Willem Heiser, 2009. "A Latent Class Multidimensional Scaling Model for Two-Way One-Mode Continuous Rating Dissimilarity Data," Psychometrika, Springer;The Psychometric Society, vol. 74(2), pages 297-315, June.
    28. Paolo Giordani & Henk Kiers, 2012. "FINDCLUS: Fuzzy INdividual Differences CLUStering," Journal of Classification, Springer;The Classification Society, vol. 29(2), pages 170-198, July.
    29. J. Fernando Vera & Rodrigo Macías, 2017. "Variance-Based Cluster Selection Criteria in a K-Means Framework for One-Mode Dissimilarity Data," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 275-294, June.
    30. Roberto Rocci & Maurizio Vichi, 2005. "Three-Mode Component Analysis with Crisp or Fuzzy Partition of Units," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 715-736, December.

  32. Patrick Groenen & Willem Heiser, 1996. "The tunneling method for global optimization in multidimensional scaling," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 529-550, September.

    Cited by:

    1. S. Hess & E. Suárez & J. Camacho & G. Ramírez & B. Hernández, 2001. "Reliability of Coordinates Obtained by MINISSA Concerning the Order of Presented Stimuli," Quality & Quantity: International Journal of Methodology, Springer, vol. 35(2), pages 117-128, May.
    2. Marc Robini & Pierre-Jean Reissman, 2013. "From simulated annealing to stochastic continuation: a new trend in combinatorial optimization," Journal of Global Optimization, Springer, vol. 56(1), pages 185-215, May.
    3. Hua Zhou & Kenneth L. Lange, 2010. "On the Bumpy Road to the Dominant Mode," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(4), pages 612-631, December.
    4. Michael Brusco & Stephanie Stahl, 2005. "Optimal Least-Squares Unidimensional Scaling: Improved Branch-and-Bound Procedures and Comparison to Dynamic Programming," Psychometrika, Springer;The Psychometric Society, vol. 70(2), pages 253-270, June.
    5. Groenen, P.J.F. & van de Velden, M., 2004. "Multidimensional scaling," Econometric Institute Research Papers EI 2004-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Groenen, Patrick J. F. & Franses, Philip Hans, 2000. "Visualizing time-varying correlations across stock markets," Journal of Empirical Finance, Elsevier, vol. 7(2), pages 155-172, August.
    7. Malone, Samuel W. & Tarazaga, Pablo & Trosset, Michael W., 2002. "Better initial configurations for metric multidimensional scaling," Computational Statistics & Data Analysis, Elsevier, vol. 41(1), pages 143-156, November.
    8. Michael Brusco & Hans-Friedrich Köhn & Stephanie Stahl, 2008. "Heuristic Implementation of Dynamic Programming for Matrix Permutation Problems in Combinatorial Data Analysis," Psychometrika, Springer;The Psychometric Society, vol. 73(3), pages 503-522, September.
    9. Michael Brusco & Hannah J Stolze & Michaela Hoffman & Douglas Steinley, 2017. "A simulated annealing heuristic for maximum correlation core/periphery partitioning of binary networks," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-17, May.
    10. Leung, Pui Lam & Lau, Kin-nam, 2004. "Estimating the city-block two-dimensional scaling model with simulated annealing," European Journal of Operational Research, Elsevier, vol. 158(2), pages 518-524, October.
    11. Groenen, P.J.F. & Kaymak, U. & van Rosmalen, J.M., 2006. "Fuzzy clustering with Minkowski distance," Econometric Institute Research Papers EI 2006-24, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Michael Brusco & Douglas Steinley, 2011. "A Tabu-Search Heuristic for Deterministic Two-Mode Blockmodeling of Binary Network Matrices," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 612-633, October.
    13. Michael Brusco & Patrick Doreian, 2015. "An Exact Algorithm for the Two-Mode KL-Means Partitioning Problem," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 481-515, October.
    14. Michael Brusco & Stephanie Stahl, 2001. "An interactive multiobjective programming approach to combinatorial data analysis," Psychometrika, Springer;The Psychometric Society, vol. 66(1), pages 5-24, March.
    15. Groenen, P.J.F. & Borg, I., 2013. "The Past, Present, and Future of Multidimensional Scaling," Econometric Institute Research Papers EI 2013-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. van den Burg, G.J.J. & Groenen, P.J.F., 2014. "GenSVM: A Generalized Multiclass Support Vector Machine," Econometric Institute Research Papers EI 2014-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  33. Henk Kiers & Patrick Groenen, 1996. "A monotonically convergent algorithm for orthogonal congruence rotation," Psychometrika, Springer;The Psychometric Society, vol. 61(2), pages 375-389, June.

    Cited by:

    1. Raoul Pietersz & Patrick J. F. Groenen, 2005. "Rank Reduction of Correlation Matrices by Majorization," Finance 0502006, University Library of Munich, Germany.
    2. Groenen, P.J.F. & Winsberg, S. & Rodriguez, O. & Diday, E., 2005. "SymScal: symbolic multidimensional scaling of interval dissimilarities," Econometric Institute Research Papers EI 2005-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Jos Berge, 2005. "J.C. Gower and G.B. Dijksterhuis.Procrustes problems. New York: Oxford University Press," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 799-801, December.
    4. K. Van Deun & P. J. F. Groenen, 2005. "Majorization Algorithms for Inspecting Circles, Ellipses, Squares, Rectangles, and Rhombi," Operations Research, INFORMS, vol. 53(6), pages 957-967, December.
    5. Groenen, P.J.F. & Winsberg, S. & Rodriguez, O. & Diday, E., 2006. "I-Scal: Multidimensional scaling of interval dissimilarities," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 360-378, November.

  34. Patrick Groenen & Rudolf Mathar & Willem Heiser, 1995. "The majorization approach to multidimensional scaling for Minkowski distances," Journal of Classification, Springer;The Classification Society, vol. 12(1), pages 3-19, March.

    Cited by:

    1. Andrew Webb, 1997. "Radial basis functions for exploratory data analysis: An iterative majorisation approach for Minkowski distances based on multidimensional scaling," Journal of Classification, Springer;The Classification Society, vol. 14(2), pages 249-267, September.
    2. Julius Žilinskas, 2012. "Parallel branch and bound for multidimensional scaling with city-block distances," Journal of Global Optimization, Springer, vol. 54(2), pages 261-274, October.
    3. Patrick Groenen & Willem Heiser, 1996. "The tunneling method for global optimization in multidimensional scaling," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 529-550, September.
    4. Antanas Žilinskas & Julius Žilinskas, 2008. "A hybrid method for multidimensional scaling using city-block distances," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 68(3), pages 429-443, December.
    5. K. Van Deun & P. J. F. Groenen, 2005. "Majorization Algorithms for Inspecting Circles, Ellipses, Squares, Rectangles, and Rhombi," Operations Research, INFORMS, vol. 53(6), pages 957-967, December.
    6. Groenen, P.J.F. & Borg, I., 2013. "The Past, Present, and Future of Multidimensional Scaling," Econometric Institute Research Papers EI 2013-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Groenen, P.J.F. & Winsberg, S. & Rodriguez, O. & Diday, E., 2006. "I-Scal: Multidimensional scaling of interval dissimilarities," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 360-378, November.

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