Representing Heterogeneity in Consumer Response Models 1996 Choice Conference Participants
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Pradeep K. Chintagunta | P. Lenk | W. DeSarbo | K. Srinivasan | M. Wedel | Kamel Jedidi | Asim Ansari | W. Kamakura | Richard M. Johnson | Pradeep Chintagunta | C. Himmelberg
[1] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[2] C. Mitchell Dayton,et al. The Nature and Use of State Mastery Models , 1980 .
[3] R. A. Boyles. On the Convergence of the EM Algorithm , 1983 .
[4] Carsten Stig Poulsen,et al. LATENT STRUCTURE ANALYSIS WITH CHOICE MODELING APPLICATIONS , 1983 .
[5] New York Dover,et al. ON THE CONVERGENCE PROPERTIES OF THE EM ALGORITHM , 1983 .
[6] Wayne S. DeSarbo,et al. Constrained classification: The use of a priori information in cluster analysis , 1984 .
[7] J. Heckman,et al. A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data , 1984 .
[8] Michael R. Hagerty,et al. Improving the Predictive Power of Conjoint Analysis: The use of Factor Analysis and Cluster Analysis , 1985 .
[9] Fionn Murtagh,et al. Cluster Dissection and Analysis: Theory, Fortran Programs, Examples. , 1986 .
[10] A. F. Smith,et al. Statistical analysis of finite mixture distributions , 1986 .
[11] W. Kamakura. A Least Squares Procedure for Benefit Segmentation with Conjoint Experiments , 1988 .
[12] M. Wedel,et al. A fuzzy clusterwise regression approach to benefit segmentation , 1989 .
[13] M. Wedel,et al. Consumer benefit segmentation using clusterwise linear regression , 1989 .
[14] Wayne S. DeSarbo,et al. A simulated annealing methodology for clusterwise linear regression , 1989 .
[15] Scott L. Zeger,et al. Generalized linear models with random e ects: a Gibbs sampling approach , 1991 .
[16] Pradeep K. Chintagunta,et al. Investigating Heterogeneity in Brand Preferences in Logit Models for Panel Data , 1991 .
[17] M. Karim. Generalized Linear Models With Random Effects , 1991 .
[18] M. Wedel,et al. A Clusterwise Regression Method for Simultaneous Fuzzy Market Structuring and Benefit Segmentation , 1991 .
[19] Michel Wedel,et al. Concomitant Variable Latent Class Models for the External Analysis of Choice Data , 1992 .
[20] U. Böckenholt. A latent-class regression approach for the analysis of recurrent choice data , 1993 .
[21] Füsun F. Gönül,et al. Modeling Multiple Sources of Heterogeneity in Multinomial Logit Models: Methodological and Managerial Issues , 1993 .
[22] Kannan Srinivasan,et al. Consumer Purchase Behavior in a frequently Bought Product Category: Estimation Issues and Managerial Insights from a Hazard Function Model with Heterogeneity , 1993 .
[23] Pradeep K. Chintagunta,et al. On Using Demographic Variables to Determine Segment Membership in Logit Mixture Models , 1994 .
[24] W. DeSarbo,et al. A Disaggregate Negative Binomial Regression Procedure for Count Data Analysis , 1994 .
[25] Michel Wedel,et al. Concomitant Variable Latent Class Models for Conjoint Analysis , 1994 .
[26] Steven H. Cohen,et al. Market segmentation with choice-based conjoint analysis , 1995 .
[27] R. Rust,et al. Model selection criteria: an investigation of relative accuracy, posterior probabilities, and combinations of criteria , 1995 .
[28] W. DeSarbo,et al. A mixture likelihood approach for generalized linear models , 1995 .
[29] W. Kamakura,et al. Modeling Preference and Structural Heterogeneity in Consumer Choice , 1996 .
[30] Peter Green,et al. Markov chain Monte Carlo in Practice , 1996 .
[31] L. Gary,et al. ABELL F. Dereck, Defining The Business. The Starting Point of Strategic Planning . USA, Prentice Hall, Englewood Cliffs, New Jersey, 1980. , 1996 .
[32] Paul E. Green,et al. Modifying Cluster-Based Segments to Enhance Agreement with an Exogenous Response Variable , 1996 .
[33] W. DeSarbo,et al. Combinatorial Optimization Approaches to Normative Market Segmentation : An Application to Industrial Market Segmentation , 1996 .
[34] Rabikar Chatterjee,et al. Joint Segmentation on Distinct Interdependent Bases with Categorical Data , 1996 .
[35] P. Lenk,et al. Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs , 1996 .
[36] Michel Wedel,et al. On Estimating Finite Mixtures of Multivariate Regression and Simultaneous Equation Models , 1996 .
[37] M. Wedel,et al. Metric Conjoint Segmentation Methods: A Monte Carlo Comparison , 1996 .
[38] W. DeSarbo,et al. Finite-Mixture Structural Equation Models for Response-Based Segmentation and Unobserved Heterogeneity , 1997 .
[39] Kamel Jedidi,et al. STEMM: A General Finite Mixture Structural Equation Model , 1997 .
[40] Peter E. Rossi,et al. Marketing models of consumer heterogeneity , 1998 .