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FlexMix: A General Framework for Finite Mixture Models and Latent Class Regression in R

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Cited by:

  1. Naoki Sudo, 2021. "Two Latent Groups Influencing Subjective Social Status: Middle Class Tendency and Clear Class Consciousness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 158(3), pages 1045-1064, December.
  2. Rosales-Tristancho, Abel & Brey, Raúl & Carazo, Ana F. & Brey, J. Javier, 2022. "Analysis of the barriers to the adoption of zero-emission vehicles in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 19-43.
  3. Sanjeena Subedi & Antonio Punzo & Salvatore Ingrassia & Paul McNicholas, 2013. "Clustering and classification via cluster-weighted factor analyzers," 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 5-40, March.
  4. Zeileis, Achim & Kleiber, Christian & Jackman, Simon, 2008. "Regression Models for Count Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i08).
  5. Naoki Sudo, 2020. "Two Types of Support for Redistribution of Wealth: Consistent and Inconsistent Policy Preferences," Societies, MDPI, vol. 10(2), pages 1-18, June.
  6. Frank J Infurna & Kevin J Grimm, 2018. "The Use of Growth Mixture Modeling for Studying Resilience to Major Life Stressors in Adulthood and Old Age: Lessons for Class Size and Identification and Model Selection," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 73(1), pages 148-159.
  7. Salvatore Ingrassia & Antonio Punzo, 2020. "Cluster Validation for Mixtures of Regressions via the Total Sum of Squares Decomposition," Journal of Classification, Springer;The Classification Society, vol. 37(2), pages 526-547, July.
  8. Jessica Gronsbell & Jessica Minnier & Sheng Yu & Katherine Liao & Tianxi Cai, 2019. "Automated feature selection of predictors in electronic medical records data," Biometrics, The International Biometric Society, vol. 75(1), pages 268-277, March.
  9. Oxana Krutova & Aki Koskinen & Laura Peutere & Jenni Ervasti & Marianna Virtanen & Mikko Härmä & Annina Ropponen, 2022. "A Longitudinal Study on Trajectories of Night Work and Sickness Absence among Hospital Employees," IJERPH, MDPI, vol. 19(13), pages 1-9, July.
  10. Rangan Gupta & Zinnia Mukherjee & Mike G. Tsionas & Peter Wanke, 2016. "Productive Efficiency of Connecticut Long Island Lobster Fishery Using a Finite Mixture Model," Working Papers 201614, University of Pretoria, Department of Economics.
  11. Sara Dolnicar & Friedrich Leisch, 2010. "Evaluation of structure and reproducibility of cluster solutions using the bootstrap," Marketing Letters, Springer, vol. 21(1), pages 83-101, March.
  12. Paul D. McNicholas, 2016. "Model-Based Clustering," Journal of Classification, Springer;The Classification Society, vol. 33(3), pages 331-373, October.
  13. Angelo Mazza & Antonio Punzo, 2020. "Mixtures of multivariate contaminated normal regression models," Statistical Papers, Springer, vol. 61(2), pages 787-822, April.
  14. David Plavcan & Georg J. Mayr & Achim Zeileis, 2013. "Automatic and Probabilistic Foehn Diagnosis with a Statistical Mixture Model," Working Papers 2013-22, Faculty of Economics and Statistics, Universität Innsbruck.
  15. Rainer Schlittgen, 2011. "A weighted least-squares approach to clusterwise regression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(2), pages 205-217, June.
  16. Bojing Liao & Xiang Li, 2023. "Neighborhood Environment and Affective Walking Experience: Cluster Analysis Results of a Virtual-Environment-Based Conjoint Experiment," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
  17. Spindler, Martin, 2013. "“They do know what they are doing... at least most of them.†Asymmetric Information in the (private) Disability Insurance," MEA discussion paper series 201209, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  18. Fritz, Heinrich & García-Escudero, Luis A. & Mayo-Iscar, Agustín, 2012. "tclust: An R Package for a Trimming Approach to Cluster Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i12).
  19. Seyyed Ali Zeytoon Nejad Moosavian & Barry K. Goodwin, 2021. "Flexible modelling of multivariate risks in pricing margin protection insurance: modelling portfolio risks with mixtures of mixtures," Applied Economics, Taylor & Francis Journals, vol. 53(4), pages 411-440, January.
  20. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
  21. Sarrias, Mauricio & Daziano, Ricardo, 2017. "Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i02).
  22. Chen, Cathy W.S. & Chan, Jennifer S.K. & So, Mike K.P. & Lee, Kevin K.M., 2011. "Classification in segmented regression problems," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2276-2287, July.
  23. Semhar Michael & Volodymyr Melnykov, 2016. "Finite Mixture Modeling of Gaussian Regression Time Series with Application to Dendrochronology," Journal of Classification, Springer;The Classification Society, vol. 33(3), pages 412-441, October.
  24. Dolnicar, Sara & Grün, Bettina & Leisch, Friedrich, 2016. "Increasing sample size compensates for data problems in segmentation studies," Journal of Business Research, Elsevier, vol. 69(2), pages 992-999.
  25. Chun-Yu Chang & Po-Chen Lin & Yung-Jiun Chien & Chien-Sheng Chen & Meng-Yu Wu, 2020. "Analysis of Chest-Compression Depth and Full Recoil in Two Infant Chest-Compression Techniques Performed by a Single Rescuer: Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 17(11), pages 1-17, June.
  26. Yuwen Zhao & Pauline E. W. van den Berg & Ioulia V. Ossokina & Theo A. Arentze, 2022. "Individual Momentary Experiences of Neighborhood Public Spaces: Results of a Virtual Environment Based Stated Preference Experiment," Sustainability, MDPI, vol. 14(9), pages 1-22, April.
  27. Olivier Cappé & Eric Moulines, 2009. "On‐line expectation–maximization algorithm for latent data models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 593-613, June.
  28. Rosales-Tristancho, Abel & Carazo, Ana F. & Brey, Raúl, 2021. "A study of the willingness of Spanish drivers to pay a premium for ZEVs," Energy Policy, Elsevier, vol. 149(C).
  29. Mengyu Yu & Mazie Krehbiel & Samantha Thompson & Tatjana Miljkovic, 2020. "An exploration of gender gap using advanced data science tools: actuarial research community," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 767-789, May.
  30. Thomas De Graaff & Jaap Boter & Jan Rouwendal, 2006. "Do Dutch Musea Compete Or Cooperate?," ERSA conference papers ersa06p387, European Regional Science Association.
  31. Neykov, N. & Filzmoser, P. & Dimova, R. & Neytchev, P., 2007. "Robust fitting of mixtures using the trimmed likelihood estimator," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 299-308, September.
  32. Adelchi Azzalini & Giovanna Menardi, 2016. "Density-based clustering with non-continuous data," Computational Statistics, Springer, vol. 31(2), pages 771-798, June.
  33. Floh, Arne & Zauner, Alexander & Koller, Monika & Rusch, Thomas, 2014. "Customer segmentation using unobserved heterogeneity in the perceived-value–loyalty–intentions link," Journal of Business Research, Elsevier, vol. 67(5), pages 974-982.
  34. Katarzyna Aleksandra Wόjtowicz & Sabina Hodžić, 2022. "Financial Resilience in the Face of Turbulent Times: Evidence from Poland and Croatian Cities," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
  35. Maura Mezzetti & Daniele Borzelli & Andrea d’Avella, 2022. "A Bayesian approach to model individual differences and to partition individuals: case studies in growth and learning curves," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1245-1271, December.
  36. Frick, Hannah & Strobl, Carolin & Leisch, Friedrich & Zeileis, Achim, 2012. "Flexible Rasch Mixture Models with Package psychomix," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i07).
  37. Nicolas Picard & Avner Bar-Hen, 2012. "A Criterion Based on the Mahalanobis Distance for Cluster Analysis with Subsampling," Journal of Classification, Springer;The Classification Society, vol. 29(1), pages 23-49, April.
  38. Salvatore D. Tomarchio & Paul D. McNicholas & Antonio Punzo, 2021. "Matrix Normal Cluster-Weighted Models," Journal of Classification, Springer;The Classification Society, vol. 38(3), pages 556-575, October.
  39. repec:jss:jstsof:27:i08 is not listed on IDEAS
  40. Ingrassia, Salvatore & Minotti, Simona C. & Punzo, Antonio, 2014. "Model-based clustering via linear cluster-weighted models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 159-182.
  41. Stillwater, Tai, 2011. "Comprehending Consumption: The Behavioral Basis and Implementation of Driver Feedback for Reducing Vehicle Energy Use," Institute of Transportation Studies, Working Paper Series qt2ns9p8h7, Institute of Transportation Studies, UC Davis.
  42. Tom Frans Wilderjans & Eva Gaer & Henk A. L. Kiers & Iven Mechelen & Eva Ceulemans, 2017. "Principal Covariates Clusterwise Regression (PCCR): Accounting for Multicollinearity and Population Heterogeneity in Hierarchically Organized Data," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 86-111, March.
  43. Lebret, Rémi & Iovleff, Serge & Langrognet, Florent & Biernacki, Christophe & Celeux, Gilles & Govaert, Gérard, 2015. "Rmixmod: The R Package of the Model-Based Unsupervised, Supervised, and Semi-Supervised Classification Mixmod Library," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i06).
  44. Salvatore Ingrassia & Simona Minotti & Giorgio Vittadini, 2012. "Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions," Journal of Classification, Springer;The Classification Society, vol. 29(3), pages 363-401, October.
  45. Qingguo Tang & R. J. Karunamuni, 2018. "Robust variable selection for finite mixture regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(3), pages 489-521, June.
  46. Franko, Mitja & Nagode, Marko, 2015. "Probability density function of the equivalent stress amplitude using statistical transformation," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 118-125.
  47. Ian Wadsworth & Lisa V. Hampson & Thomas Jaki & Graeme J. Sills & Anthony G. Marson & Richard Appleton, 2020. "A quantitative framework to inform extrapolation decisions in children," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 515-534, February.
  48. Kneib, Thomas & Silbersdorff, Alexander & Säfken, Benjamin, 2023. "Rage Against the Mean – A Review of Distributional Regression Approaches," Econometrics and Statistics, Elsevier, vol. 26(C), pages 99-123.
  49. Grün, Bettina & Kosmidis, Ioannis & Zeileis, Achim, 2012. "Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i11).
  50. Ahonen, Ilmari & Nevalainen, Jaakko & Larocque, Denis, 2019. "Prediction with a flexible finite mixture-of-regressions," Computational Statistics & Data Analysis, Elsevier, vol. 132(C), pages 212-224.
  51. Wu, Yinglu & Wu, Jianan, 2016. "The Impact of User Review Volume on Consumers' Willingness-to-Pay: A Consumer Uncertainty Perspective," Journal of Interactive Marketing, Elsevier, vol. 33(C), pages 43-56.
  52. Dunstan, Piers K. & Foster, Scott D. & Darnell, Ross, 2011. "Model based grouping of species across environmental gradients," Ecological Modelling, Elsevier, vol. 222(4), pages 955-963.
  53. Proust-Lima, Cécile & Philipps, Viviane & Liquet, Benoit, 2017. "Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i02).
  54. repec:mea:meawpa:12260 is not listed on IDEAS
  55. Thomas de Graaff & Jaap Boter & Jan Rouwendal, 2009. "On Spatial Differences in the Attractiveness of Dutch Museums," Environment and Planning A, , vol. 41(11), pages 2778-2797, November.
  56. Wang, Po-Chieh & Hsu, Yu-Ting & Hsu, Chia-Wei, 2021. "Analysis of waiting time perception of bus passengers provided with mobile service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 319-336.
  57. Youmi Suk & Jee-Seon Kim & Hyunseung Kang, 2021. "Hybridizing Machine Learning Methods and Finite Mixture Models for Estimating Heterogeneous Treatment Effects in Latent Classes," Journal of Educational and Behavioral Statistics, , vol. 46(3), pages 323-347, June.
  58. Jennifer S. K. Chan & S. T. Boris Choy & Udi Makov & Ariel Shamir & Vered Shapovalov, 2022. "Variable Selection Algorithm for a Mixture of Poisson Regression for Handling Overdispersion in Claims Frequency Modeling Using Telematics Car Driving Data," Risks, MDPI, vol. 10(4), pages 1-10, April.
  59. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
  60. Roberto Mari & Salvatore Ingrassia & Antonio Punzo, 2023. "Local and Overall Deviance R-Squared Measures for Mixtures of Generalized Linear Models," Journal of Classification, Springer;The Classification Society, vol. 40(2), pages 233-266, July.
  61. Utkarsh J. Dang & Antonio Punzo & Paul D. McNicholas & Salvatore Ingrassia & Ryan P. Browne, 2017. "Multivariate Response and Parsimony for Gaussian Cluster-Weighted Models," Journal of Classification, Springer;The Classification Society, vol. 34(1), pages 4-34, April.
  62. Bettina Grün & Friedrich Leisch, 2008. "Identifiability of Finite Mixtures of Multinomial Logit Models with Varying and Fixed Effects," Journal of Classification, Springer;The Classification Society, vol. 25(2), pages 225-247, November.
  63. Ciarleglio, Adam & Todd Ogden, R., 2016. "Wavelet-based scalar-on-function finite mixture regression models," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 86-96.
  64. White, Arthur & Murphy, Thomas Brendan, 2014. "BayesLCA: An R Package for Bayesian Latent Class Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i13).
  65. Xavier Bry & Ndèye Niang & Thomas Verron & Stéphanie Bougeard, 2023. "Clusterwise elastic-net regression based on a combined information criterion," 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. 17(1), pages 75-107, March.
  66. Brianna JeeWon Paulich & V. Kumar, 2021. "Relating entertainment features in screenplays to movie performance: an empirical investigation," Journal of the Academy of Marketing Science, Springer, vol. 49(6), pages 1222-1242, November.
  67. Peter Willemé, 2017. "Working Paper 14-17 - Modelling unobserved heterogeneity in distribution - Finite mixtures of the Johnson family of distributions," Working Papers 1714, Federal Planning Bureau, Belgium.
  68. repec:jss:jstsof:42:i10 is not listed on IDEAS
  69. Omerovic, Sanela & Friedl, Herwig & Grün, Bettina, 2022. "Modelling Multiple Regimes in Economic Growth by Mixtures of Generalised Nonlinear Models," Econometrics and Statistics, Elsevier, vol. 22(C), pages 124-135.
  70. Raoofpanah, Iman & Zamudio, César & Groening, Christopher, 2023. "Review reader segmentation based on the heterogeneous impacts of review and reviewer attributes on review helpfulness: A study involving ZIP code data," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
  71. Salvatore Ingrassia & Simona Minotti & Giorgio Vittadini, 2012. "Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions," Journal of Classification, Springer;The Classification Society, vol. 29(3), pages 363-401, October.
  72. Maik Dehnert & Josephine Schumann, 2022. "Uncovering the digitalization impact on consumer decision-making for checking accounts in banking," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1503-1528, September.
  73. Marc A. Scott & Kaushik Mohan & Jacques‐Antoine Gauthier, 2020. "Model‐based clustering and analysis of life history data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1231-1251, June.
  74. Maureen Lankhuizen & Thomas De Graaff & Henri De Groot, 2012. "Product Heterogeneity, Intangible Barriers & Distance Decay: The effect of multiple dimensions of distance on trade across different product categories," ERSA conference papers ersa12p151, European Regional Science Association.
  75. Rischatsch, Maurus, 2015. "Who joins the network? Physicians’ resistance to take budgetary co-responsibility," Journal of Health Economics, Elsevier, vol. 40(C), pages 109-121.
  76. Marc Gürtler & Marvin Zöllner, 2023. "Heterogeneities among credit risk parameter distributions: the modality defines the best estimation method," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 251-287, March.
  77. Artur Wolak & Kamil Fijorek & Grzegorz Zając, 2020. "Professional Car Drivers’ Attitudes toward Technical, Marketing and Environmental Characteristics of Engine Oils: A Survey Study," Energies, MDPI, vol. 13(8), pages 1-14, April.
  78. Michiel van Leuvensteijn & Thomas de Graaff, 2007. "The impact of housing market institutions on labour mobility; a European cross-country comparison," CPB Discussion Paper 82.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
  79. Anindita Chakravarty & Rajdeep Grewal & V. Sambamurthy, 2013. "Information Technology Competencies, Organizational Agility, and Firm Performance: Enabling and Facilitating Roles," Information Systems Research, INFORMS, vol. 24(4), pages 976-997, December.
  80. Fabian Dvorak, 2020. "stratEst: Strategy Estimation in R," TWI Research Paper Series 119, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
  81. Sanjeena Subedi & Antonio Punzo & Salvatore Ingrassia & Paul McNicholas, 2015. "Cluster-weighted $$t$$ t -factor analyzers for robust model-based clustering and dimension reduction," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(4), pages 623-649, November.
  82. Shusaku Tsumoto & Tomohiro Kimura & Shoji Hirano, 2021. "Mining Clinical Pathways Using Dual Clustering," The Review of Socionetwork Strategies, Springer, vol. 15(2), pages 287-307, November.
  83. Ceren Ozgen & Thomas de Graff, 2013. "Sorting out the impact of cultural diversity on innovative firms. An empirical analysis of Dutch micro-data," Norface Discussion Paper Series 2013012, Norface Research Programme on Migration, Department of Economics, University College London.
  84. Jessica H. Belle & Howard H. Chang & Yujie Wang & Xuefei Hu & Alexei Lyapustin & Yang Liu, 2017. "The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM 2.5 Mass and Composition," IJERPH, MDPI, vol. 14(10), pages 1-15, October.
  85. Robin, Stéphane & Scrucca, Luca, 2023. "Mixture-based estimation of entropy," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
  86. Decker, Reinhold & Trusov, Michael, 2010. "Estimating aggregate consumer preferences from online product reviews," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 293-307.
  87. Hui Ye & Anthony Bellotti, 2019. "Modelling Recovery Rates for Non-Performing Loans," Risks, MDPI, vol. 7(1), pages 1-17, February.
  88. Chun-Yu Chang & Yueh-Tseng Hou & Yung-Jiun Chien & Yu-Long Chen & Po-Chen Lin & Chien-Sheng Chen & Meng-Yu Wu, 2020. "Two-Thumb or Two-Finger Technique in Infant Cardiopulmonary Resuscitation by a Single Rescuer? A Meta-Analysis with GOSH Analysis," IJERPH, MDPI, vol. 17(14), pages 1-19, July.
  89. Fernandez-Blanco, Victor & Orea, Luis & Prieto-Rodriguez, Juan, 2009. "Analyzing consumers heterogeneity and self-reported tastes: An approach consistent with the consumer's decision making process," Journal of Economic Psychology, Elsevier, vol. 30(4), pages 622-633, August.
  90. Yang Zhang & Yidong Peng & Xiuli Qu & Jing Shi & Ergin Erdem, 2021. "A Finite Mixture GARCH Approach with EM Algorithm for Energy Forecasting Applications," Energies, MDPI, vol. 14(9), pages 1-22, April.
  91. Abhinandan Dalal & Diganta Mukherjee & Subhrajyoty Roy, 2020. "The Information Content of Taster's Valuation in Tea Auctions of India," Papers 2005.02814, arXiv.org.
  92. Prates, Marcos Oliveira & Lachos, Victor Hugo & Barbosa Cabral, Celso Rômulo, 2013. "mixsmsn: Fitting Finite Mixture of Scale Mixture of Skew-Normal Distributions," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 54(i12).
  93. Nicolas Städler & Peter Bühlmann & Sara Geer, 2010. "ℓ 1 -penalization for mixture regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(2), pages 209-256, August.
  94. Maureen B. M. Lankhuizen & Thomas De Graaff & Henri L. F. de Groot, 2015. "Product Heterogeneity, Intangible Barriers and Distance Decay: The Effect of Multiple Dimensions of Distance on Trade across Different Product Categories," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(2), pages 137-159, June.
  95. Aleksey Min & Matthias Scherer & Amelie Schischke & Rudi Zagst, 2020. "Modeling Recovery Rates of Small- and Medium-Sized Entities in the US," Mathematics, MDPI, vol. 8(11), pages 1-18, October.
  96. Spindler, M., 2014. "“They do know what they are doing ... at least most of them.†Asymmetric Information in the (private) Disability Insurance," Health, Econometrics and Data Group (HEDG) Working Papers 14/16, HEDG, c/o Department of Economics, University of York.
  97. Papastamoulis, Panagiotis & Martin-Magniette, Marie-Laure & Maugis-Rabusseau, Cathy, 2016. "On the estimation of mixtures of Poisson regression models with large number of components," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 97-106.
  98. Sonja Radas & Drazen Prelec, 2019. "Whose data can we trust: How meta-predictions can be used to uncover credible respondents in survey data," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-16, December.
  99. Wayne S. DeSarbo & Qian Chen & Ashley Stadler Blank, 2017. "A Parametric Constrained Segmentation Methodology for Application in Sport Marketing," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 4(4), pages 37-55, December.
  100. Krzysztof Rusek & Agnieszka Kleszcz & Albert Cabellos-Aparicio, 2023. "Bayesian inference of spatial and temporal relations in AI patents for EU countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3313-3335, June.
  101. Luca Bagnato & Antonio Punzo, 2013. "Finite mixtures of unimodal beta and gamma densities and the $$k$$ -bumps algorithm," Computational Statistics, Springer, vol. 28(4), pages 1571-1597, August.
  102. Boris Branisa & Adriana Cardozo, 2009. "Revisiting the Regional Growth Convergence Debate in Colombia Using Income Indicators," Ibero America Institute for Econ. Research (IAI) Discussion Papers 194, Ibero-America Institute for Economic Research, revised 21 Aug 2009.
  103. Grun, Bettina & Leisch, Friedrich, 2007. "Fitting finite mixtures of generalized linear regressions in R," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5247-5252, July.
  104. Paul Mills & César Zamudio, 2018. "Scanning for discounts: examining the redemption of competing mobile coupons," Journal of the Academy of Marketing Science, Springer, vol. 46(5), pages 964-982, September.
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