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A maximum likelihood methodology for clusterwise linear regression

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  1. Gianfranco DI VAIO & Michele BATTISTI, 2010. "A Spatially-Filtered Mixture of Beta-Convergence Regression for EU Regions, 1980-2002," Regional and Urban Modeling 284100013, EcoMod.
  2. 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.
  3. Antonio Punzo & Paul. D. McNicholas, 2017. "Robust Clustering in Regression Analysis via the Contaminated Gaussian Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 34(2), pages 249-293, July.
  4. Michael P. B. Gallaugher & Salvatore D. Tomarchio & Paul D. McNicholas & Antonio Punzo, 2022. "Multivariate cluster weighted models using skewed distributions," 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(1), pages 93-124, March.
  5. Frenkel Ter Hofstede & Michel Wedel & Jan-Benedict E.M. Steenkamp, 2002. "Identifying Spatial Segments in International Markets," Marketing Science, INFORMS, vol. 21(2), pages 160-177, July.
  6. Kaposty, Florian & Kriebel, Johannes & Löderbusch, Matthias, 2020. "Predicting loss given default in leasing: A closer look at models and variable selection," International Journal of Forecasting, Elsevier, vol. 36(2), pages 248-266.
  7. Meldrum, James R., 2015. "Comparing different attitude statements in latent class models of stated preferences for managing an invasive forest pathogen," Ecological Economics, Elsevier, vol. 120(C), pages 13-22.
  8. Reis dos Santos, M. Isabel & Reis dos Santos, Pedro M., 2016. "Switching regression metamodels in stochastic simulation," European Journal of Operational Research, Elsevier, vol. 251(1), pages 142-147.
  9. Yu Ding & Wayne S. DeSarbo & Dominique M. Hanssens & Kamel Jedidi & John G. Lynch & Donald R. Lehmann, 2020. "The past, present, and future of measurement and methods in marketing analysis," Marketing Letters, Springer, vol. 31(2), pages 175-186, September.
  10. Michele Battisti & Filippo Belloc & Massimo Del Gatto, 2015. "Unbundling Technology Adoption and tfp at the Firm Level: Do Intangibles Matter?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 24(2), pages 390-414, June.
  11. 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.
  12. Guochang Wang, 2017. "Dimension reduction in functional regression with categorical predictor," Computational Statistics, Springer, vol. 32(2), pages 585-609, June.
  13. Philip Kostov & Sophia Davidova, 2023. "Smallholders Are Not the Same: Under the Hood of Kosovo Agriculture," Land, MDPI, vol. 12(1), pages 1-16, January.
  14. 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.
  15. Hennig, Christian, 2003. "Clusters, outliers, and regression: fixed point clusters," Journal of Multivariate Analysis, Elsevier, vol. 86(1), pages 183-212, July.
  16. Nicolas Depraetere & Martina Vandebroek, 2014. "Order selection in finite mixtures of linear regressions," Statistical Papers, Springer, vol. 55(3), pages 871-911, August.
  17. Adil M. Bagirov & Julien Ugon & Hijran G. Mirzayeva, 2015. "Nonsmooth Optimization Algorithm for Solving Clusterwise Linear Regression Problems," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 755-780, March.
  18. Duncan Fong & Sunghoon Kim & Zhe Chen & Wayne DeSarbo, 2016. "A Bayesian Multinomial Probit MODEL FOR THE ANALYSIS OF PANEL CHOICE DATA," Psychometrika, Springer;The Psychometric Society, vol. 81(1), pages 161-183, March.
  19. 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.
  20. Michele Battisti & Filippo Belloc & Massimo Del Gatto, 2017. "Technology-specific Production Functions," Working Paper series 17-26, Rimini Centre for Economic Analysis.
  21. Bouveyron, C. & Girard, S. & Schmid, C., 2007. "High-dimensional data clustering," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 502-519, September.
  22. Vincent Boucher & Carlo L. Del Bello & Fabrizio Panebianco & Thierry Verdier & Yves Zenou, 2023. "Education Transmission and Network Formation," Journal of Labor Economics, University of Chicago Press, vol. 41(1), pages 129-173.
  23. Gabriele Perrone & Gabriele Soffritti, 2023. "Seemingly unrelated clusterwise linear regression for contaminated data," Statistical Papers, Springer, vol. 64(3), pages 883-921, June.
  24. Hsu, David, 2015. "Comparison of integrated clustering methods for accurate and stable prediction of building energy consumption data," Applied Energy, Elsevier, vol. 160(C), pages 153-163.
  25. Martínez-Zarzoso, Inmaculada & Maruotti, Antonello, 2011. "The impact of urbanization on CO2 emissions: Evidence from developing countries," Ecological Economics, Elsevier, vol. 70(7), pages 1344-1353, May.
  26. Wang, Shaoli & Huang, Mian & Wu, Xing & Yao, Weixin, 2016. "Mixture of functional linear models and its application to CO2-GDP functional data," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 1-15.
  27. Rajdeep Grewal & Gary L. Lilien & Girish Mallapragada, 2006. "Location, Location, Location: How Network Embeddedness Affects Project Success in Open Source Systems," Management Science, INFORMS, vol. 52(7), pages 1043-1056, July.
  28. Réal Carbonneau & Gilles Caporossi & Pierre Hansen, 2014. "Globally Optimal Clusterwise Regression By Column Generation Enhanced with Heuristics, Sequencing and Ending Subset Optimization," Journal of Classification, Springer;The Classification Society, vol. 31(2), pages 219-241, July.
  29. Pennings, Joost M.E. & Garcia, Philip & Irwin, Scott H. & Good, Darrel L., 2003. "How To Group Market Participants? Heterogeneity In Hedging Behavior," 2003 Annual meeting, July 27-30, Montreal, Canada 21963, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  30. 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.
  31. Carbonneau, Réal A. & Caporossi, Gilles & Hansen, Pierre, 2011. "Globally optimal clusterwise regression by mixed logical-quadratic programming," European Journal of Operational Research, Elsevier, vol. 212(1), pages 213-222, July.
  32. Michele Battisti & Gianfranco Vaio, 2009. "A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002," Studies in Empirical Economics, in: Giuseppe Arbia & Badi H. Baltagi (ed.), Spatial Econometrics, pages 105-121, Springer.
  33. Larcker, David F., 2003. "Discussion of "are executive stock options associated with future earnings?"," Journal of Accounting and Economics, Elsevier, vol. 36(1-3), pages 91-103, December.
  34. David F. Larcker & Scott A. Richardson, 2004. "Fees Paid to Audit Firms, Accrual Choices, and Corporate Governance," Journal of Accounting Research, Wiley Blackwell, vol. 42(3), pages 625-658, June.
  35. De la Cruz-Mesia, Rolando & Quintana, Fernando A. & Marshall, Guillermo, 2008. "Model-based clustering for longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1441-1457, January.
  36. Sphiwe B. Skhosana & Salomon M. Millard & Frans H. J. Kanfer, 2023. "A Novel EM-Type Algorithm to Estimate Semi-Parametric Mixtures of Partially Linear Models," Mathematics, MDPI, vol. 11(5), pages 1-20, February.
  37. Francesca Torti & Marco Riani & Gianluca Morelli, 2021. "Semiautomatic robust regression clustering of international trade data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 863-894, September.
  38. Renato Cordeiro Amorim, 2016. "A Survey on Feature Weighting Based K-Means Algorithms," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 210-242, July.
  39. Fei Liu & L. Billard, 2022. "Partition of Interval-Valued Observations Using Regression," Journal of Classification, Springer;The Classification Society, vol. 39(1), pages 55-77, March.
  40. Gianfranco Di Vaio & Kerstin Enflo, 2009. "Did Globalization Lead to Segmentation? Identifying Cross-Country Growth Regimes in the Long-Run," Working Papers CELEG 0902, Dipartimento di Economia e Finanza, LUISS Guido Carli.
  41. 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.
  42. Hye Suk & Heungsun Hwang, 2010. "Regularized fuzzy clusterwise ridge regression," 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. 4(1), pages 35-51, April.
  43. L. A. García‐Escudero & A. Gordaliza & R. San Martín & S. Van Aelst & R. Zamar, 2009. "Robust linear clustering," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(1), pages 301-318, January.
  44. Francesco Dotto & Alessio Farcomeni & Luis Angel García-Escudero & Agustín Mayo-Iscar, 2017. "A fuzzy approach to robust regression clustering," 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(4), pages 691-710, December.
  45. Kamel Jedidi & Venkatram Ramaswamy & Wayne Desarbo, 1993. "A maximum likelihood method for latent class regression involving a censored dependent variable," Psychometrika, Springer;The Psychometric Society, vol. 58(3), pages 375-394, September.
  46. Chiheb-Eddine N’Cir & Nadia Essoussi & Mohamed Limam, 2015. "Kernel-Based Methods to Identify Overlapping Clusters with Linear and Nonlinear Boundaries," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 176-211, July.
  47. Villani, Mattias & Kohn, Robert & Nott, David J., 2012. "Generalized smooth finite mixtures," Journal of Econometrics, Elsevier, vol. 171(2), pages 121-133.
  48. Li, Ran & Wang, Zhimin & Gu, Chenghong & Li, Furong & Wu, Hao, 2016. "A novel time-of-use tariff design based on Gaussian Mixture Model," Applied Energy, Elsevier, vol. 162(C), pages 1530-1536.
  49. Simon Blanchard & Daniel Aloise & Wayne DeSarbo, 2012. "The Heterogeneous P-Median Problem for Categorization Based Clustering," Psychometrika, Springer;The Psychometric Society, vol. 77(4), pages 741-762, October.
  50. Heungsun Hwang & Marc Tomiuk, 2010. "Fuzzy clusterwise quasi-likelihood generalized linear models," 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. 4(4), pages 255-270, December.
  51. Michele Battisti & Filippo Belloc & Massimo Del Gatto, 2020. "Labor Productivity and Firm-Level TFP with Technology-Specific Production Function," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 35, pages 283-300, January.
  52. Pennings, Joost M. E. & Garcia, Philip, 2004. "Hedging behavior in small and medium-sized enterprises: The role of unobserved heterogeneity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 951-978, May.
  53. Bengt Muthén & Tihomir Asparouhov, 2009. "Multilevel regression mixture analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 639-657, June.
  54. Mirfarah, Elham & Naderi, Mehrdad & Chen, Ding-Geng, 2021. "Mixture of linear experts model for censored data: A novel approach with scale-mixture of normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
  55. Giuliano Galimberti & Gabriele Soffritti, 2020. "Seemingly unrelated clusterwise linear regression," 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. 14(2), pages 235-260, June.
  56. Teague R. Henry & Kathleen M. Gates & Mitchell J. Prinstein & Douglas Steinley, 2020. "Modeling Heterogeneous Peer Assortment Effects Using Finite Mixture Exponential Random Graph Models," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 8-34, March.
  57. Cremaschini, Alessandro & Maruotti, Antonello, 2023. "A finite mixture analysis of structural breaks in the G-7 gross domestic product series," Research in Economics, Elsevier, vol. 77(1), pages 76-90.
  58. 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.
  59. Stéphanie Bougeard & Hervé Abdi & Gilbert Saporta & Ndèye Niang, 2018. "Clusterwise analysis for multiblock component methods," 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(2), pages 285-313, June.
  60. Jan-Michael Becker & Christian Ringle & Marko Sarstedt & Franziska Völckner, 2015. "How collinearity affects mixture regression results," Marketing Letters, Springer, vol. 26(4), pages 643-659, December.
  61. Di Vaio, Gianfranco & Enflo, Kerstin, 2011. "Did globalization drive convergence? Identifying cross-country growth regimes in the long run," European Economic Review, Elsevier, vol. 55(6), pages 832-844, August.
  62. Garlipp, T. & Muller, C.H., 2006. "Detection of linear and circular shapes in image analysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1479-1490, December.
  63. Angelo Mazza & Antonio Punzo, 2020. "Mixtures of multivariate contaminated normal regression models," Statistical Papers, Springer, vol. 61(2), pages 787-822, April.
  64. 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.
  65. 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.
  66. Francesca Torti & Domenico Perrotta & Marco Riani & Andrea Cerioli, 2019. "Assessing trimming methodologies for clustering linear regression 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. 13(1), pages 227-257, March.
  67. Wu, Qiang & Yao, Weixin, 2016. "Mixtures of quantile regressions," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 162-176.
  68. 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.
  69. Jianan Wu & Wayne DeSarbo & Pu-Ju Chen & Yao-Yi Fu, 2006. "A latent structure factor analytic approach for customer satisfaction measurement," Marketing Letters, Springer, vol. 17(3), pages 221-238, July.
  70. 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.
  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. Bagirov, Adil M. & Ugon, Julien & Mirzayeva, Hijran, 2013. "Nonsmooth nonconvex optimization approach to clusterwise linear regression problems," European Journal of Operational Research, Elsevier, vol. 229(1), pages 132-142.
  73. Gianfranco Di Vaio & Kerstin Enflo, 2009. "Did globalisation lead to segmentation? Identifying cross-country growth regimes in the long-run, 1870-2003," Working Papers 9013, Economic History Society.
  74. Joki, Kaisa & Bagirov, Adil M. & Karmitsa, Napsu & Mäkelä, Marko M. & Taheri, Sona, 2020. "Clusterwise support vector linear regression," European Journal of Operational Research, Elsevier, vol. 287(1), pages 19-35.
  75. Van Aelst, Stefan & (Steven) Wang, Xiaogang & Zamar, Ruben H. & Zhu, Rong, 2006. "Linear grouping using orthogonal regression," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1287-1312, March.
  76. Ana Oliveira-Brochado & Francisco Vitorino Martins, 2008. "Segmentação de Mercado e modelos mistura de regressão para variáveis normais," FEP Working Papers 262, Universidade do Porto, Faculdade de Economia do Porto.
  77. Leisch, Friedrich, 2004. "FlexMix: A General Framework for Finite Mixture Models and Latent Class Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i08).
  78. Gerhard Arminger & Petra Stein, 1997. "Finite Mixtures of Covariance Structure Models with Regressors," Sociological Methods & Research, , vol. 26(2), pages 148-182, November.
  79. Pennings, Joost M.E. & Garcia, Philip & Irwin, Scott H., 2011. "Accounting for Heterogeneity in Hedging Behavior: Comparing & Evaluating Grouping Methods," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114787, European Association of Agricultural Economists.
  80. Grewal, Rajdeep & Chakravarty, Anindita & Ding, Min & Liechty, John, 2008. "Counting chickens before the eggs hatch: Associating new product development portfolios with shareholder expectations in the pharmaceutical sector," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 261-272.
  81. Preda, C. & Saporta, G., 2005. "Clusterwise PLS regression on a stochastic process," Computational Statistics & Data Analysis, Elsevier, vol. 49(1), pages 99-108, April.
  82. 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.
  83. repec:jss:jstsof:11:i08 is not listed on IDEAS
  84. 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.
  85. Wu, Qiang & Sampson, Allan R., 2009. "Mixture modeling with applications in schizophrenia research," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2563-2572, May.
  86. Sanjeena Subedi & Drew Neish & Stephen Bak & Zeny Feng, 2020. "Cluster analysis of microbiome data by using mixtures of Dirichlet–multinomial regression models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1163-1187, November.
  87. 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.
  88. Casey Codd & Robert Cudeck, 2014. "Nonlinear Random-Effects Mixture Models for Repeated Measures," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 60-83, January.
  89. Hien D. Nguyen & Geoffrey J. McLachlan & Jeremy F. P. Ullmann & Andrew L. Janke, 2016. "Spatial clustering of time series via mixture of autoregressions models and Markov random fields," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 414-439, November.
  90. Wayne DeSarbo & Richard Oliver & Arvind Rangaswamy, 1989. "A simulated annealing methodology for clusterwise linear regression," Psychometrika, Springer;The Psychometric Society, vol. 54(4), pages 707-736, September.
  91. Slaets, Leen & Claeskens, Gerda & Hubert, Mia, 2012. "Phase and amplitude-based clustering for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2360-2374.
  92. Kim, Sunghoon & DeSarbo, Wayne S. & Chang, Won, 2021. "Note: A new approach to the modeling of spatially dependent and heterogeneous geographical regions," International Journal of Research in Marketing, Elsevier, vol. 38(3), pages 792-803.
  93. Michel Wedel, 2001. "Computing the Standards Errors of Mixture Model Parameters with EM when Classes are Well Separated," Computational Statistics, Springer, vol. 16(4), pages 539-558, December.
  94. Lloyd-Jones, Luke R. & Nguyen, Hien D. & McLachlan, Geoffrey J., 2018. "A globally convergent algorithm for lasso-penalized mixture of linear regression models," Computational Statistics & Data Analysis, Elsevier, vol. 119(C), pages 19-38.
  95. 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.
  96. D'Urso, Pierpaolo & Santoro, Adriana, 2006. "Fuzzy clusterwise linear regression analysis with symmetrical fuzzy output variable," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 287-313, November.
  97. Allen, Eric J. & Larson, Chad R. & Sloan, Richard G., 2013. "Accrual reversals, earnings and stock returns," Journal of Accounting and Economics, Elsevier, vol. 56(1), pages 113-129.
  98. Ana Oliveira-Brochado & Francisco Vitorino Martins, 2014. "Identifying Small Market Segments with Mixture Regression Models," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 4(4), pages 812-812.
  99. El Assaad, Hani & Samé, Allou & Govaert, Gérard & Aknin, Patrice, 2016. "A variational Expectation–Maximization algorithm for temporal data clustering," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 206-228.
  100. Atefeh Zarei & Zahra Khodadadi & Mohsen Maleki & Karim Zare, 2023. "Robust mixture regression modeling based on two-piece scale mixtures of normal distributions," 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 181-210, March.
  101. Kagie, M. & van der Loos, M.J.H.M. & van Wezel, M.C., 2008. "Including Item Characteristics in the Probabilistic Latent Semantic Analysis Model for Collaborative Filtering," ERIM Report Series Research in Management ERS-2008-053-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.
  102. Germann, Frank & Lilien, Gary L. & Rangaswamy, Arvind, 2013. "Performance implications of deploying marketing analytics," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 114-128.
  103. Li, Ting & Song, Xinyuan & Zhang, Yingying & Zhu, Hongtu & Zhu, Zhongyi, 2021. "Clusterwise functional linear regression models," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
  104. Ana Oliveira-Brochado & Francisco Vitorino Martins, 2008. "Determining the Number of Market Segments Using an Experimental Design," FEP Working Papers 263, Universidade do Porto, Faculdade de Economia do Porto.
  105. Kostov, Philip & Davidova, Sophia, 2017. "One size does not fit all: an empirical investigation of the Romanian agriculture production function," 91st Annual Conference, April 24-26, 2017, Royal Dublin Society, Dublin, Ireland 258642, Agricultural Economics Society.
  106. Duncan Fong & Wayne DeSarbo, 2007. "A Bayesian methodology for simultaneously detecting and estimating regime change points and variable selection in multiple regression models for marketing research," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 427-453, December.
  107. 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.
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