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- Publisher
- Cambridge University Press
- Copyright
- Copyright © 1999 by The Psychometric Society
- Subject
- Psychology; Psychometrics; Statistical Theory and Methods; Assessment, Testing and Evaluation; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law
- ISSN
- 0033-3123
- eISSN
- 1860-0980
- DOI
- 10.1007/bf02294568
- Publisher site
- See Article on Publisher Site
Abstract
Models and parameters of finite mixtures of multivariate normal densities conditional on regressor variables are specified and estimated. We consider mixtures of multivariate normals where the expected value for each component depends on possibly nonnormal regressor variables. The expected values and covariance matrices of the mixture components are parameterized using conditional mean- and covariance-structures. We discuss the construction of the likelihood function, estimation of the mixture model with regressors using three different EM algorithms, estimation of the asymptotic covariance matrix of parameters and testing for the number of mixture components. In addition to simulation studies, data on food preferences are analyzed.
Journal
Psychometrika – Cambridge University Press
Published: Dec 30, 2005