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

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  • I. R. Cruz-Medina
  • T. P. Hettmansperger
  • H. Thomas

Abstract

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. Copyright 2004 Royal Statistical Society.

Suggested Citation

  • I. R. Cruz-Medina & T. P. Hettmansperger & H. Thomas, 2004. "Semiparametric mixture models and repeated measures: the multinomial cut point model," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(3), pages 463-474.
  • Handle: RePEc:bla:jorssc:v:53:y:2004:i:3:p:463-474
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    References listed on IDEAS

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    1. Yosihiko Ogata & Koichi Katsura, 1988. "Likelihood analysis of spatial inhomogeneity for marked point patterns," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 40(1), pages 29-39, March.
    2. Yosihiko Ogata, 2000. "Empirical Bayes Age-Period-Cohort Analysis of Retrospective Incidence Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(3), pages 415-432.
    3. F. Musmeci & D. Vere-Jones, 1992. "A space-time clustering model for historical earthquakes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 44(1), pages 1-11, March.
    4. Yosihiko Ogata, 1998. "Space-Time Point-Process Models for Earthquake Occurrences," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 50(2), pages 379-402, June.
    5. Yosihiko Ogata, 1990. "A Monte Carlo method for an objective Bayesian procedure," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 42(3), pages 403-433, September.
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    Cited by:

    1. Hiroyuki Kasahara & Katsumi Shimotsu, 2014. "Non-parametric identification and estimation of the number of components in multivariate mixtures," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 97-111, January.

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