Semiparametric mixture models and repeated measures: the multinomial cut point model
AbstractSuppose that we have "m" repeated measures on each subject, and we model the observation vectors with a finite mixture model. We further assume that the repeated measures are conditionally independent. We present methods to estimate the shape of the component distributions along with various features of the component distributions such as the medians, means and variances. We make no distributional assumptions on the components; indeed, we allow different shapes for different components. Copyright 2004 Royal Statistical Society.
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Bibliographic InfoArticle provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society Series C.
Volume (Year): 53 (2004)
Issue (Month): 3 ()
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- Kasahara Hiroyuki & Shimotsu Katsumi, 2012.
"Nonparametric Identification and Estimation of the Number of Components in Multivariate Mixtures,"
Global COE Hi-Stat Discussion Paper Series
gd12-247, Institute of Economic Research, Hitotsubashi University.
- Hiroyuki Kasahara & Katsumi Shimotsu, 2012. "Nonparametric Identification and Estimation of the Number of Components in Multivariate Mixtures," CIRJE F-Series CIRJE-F-866, CIRJE, Faculty of Economics, University of Tokyo.
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