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Semiparametric mixture models and repeated measures: the multinomial cut point model

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Suppose 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.

Keywords: EM algorithm; Finite mixtures; Multinomial likelihood; Nonparametric estimation

Document Type: Research Article


Affiliations: 1: 1Instituto Tecnológico de Sonora, Mexico 2: 2Pennsylvania State University, University Park, USA

Publication date: 2004-08-01

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