Literature DB >> 18974843

Model Misspecification: Finite Mixture or Homogeneous?

Thaddeus Tarpey1, Dong Yun, Eva Petkova.   

Abstract

A common problem in statistical modelling is to distinguish between finite mixture distribution and a homogeneous non-mixture distribution. Finite mixture models are widely used in practice and often mixtures of normal densities are indistinguishable from homogenous non-normal densities. This paper illustrates what happens when the EM algorithm for normal mixtures is applied to a distribution that is a homogeneous non-mixture distribution. In particular, a population-based EM algorithm for finite mixtures is introduced and applied directly to density functions instead of sample data. The population-based EM algorithm is used to find finite mixture approximations to common homogeneous distributions. An example regarding the nature of a placebo response in drug treated depressed subjects is used to illustrate ideas.

Year:  2008        PMID: 18974843      PMCID: PMC2575245          DOI: 10.1177/1471082X0800800204

Source DB:  PubMed          Journal:  Stat Modelling        ISSN: 1471-082X            Impact factor:   2.039


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Authors:  E A MURPHY
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3.  Practical problems in a method of cluster analysis.

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Journal:  Biometrics       Date:  1971-09       Impact factor: 2.571

4.  Bimodality and the nature of depression.

Authors:  B S Everitt
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2.  Partitioning of Functional Data for Understanding Heterogeneity in Psychiatric Conditions.

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6.  LATENT CLASS MODELING USING MATRIX COVARIATES WITH APPLICATION TO IDENTIFYING EARLY PLACEBO RESPONDERS BASED ON EEG SIGNALS.

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7.  A statistical approach for identifying differential distributions in single-cell RNA-seq experiments.

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  7 in total

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