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On the determination of the number of components in a mixture

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  • Polymenis, A.
  • Titterington, D. M.

Abstract

A modification is proposed to a method of Windham and Cutler (1992) for determining the number of components in a mixture. An information-based eigenvalue is computed that, in theory, becomes zero as soon as too many mixture components are included in the model. In a simulation exercise, the method appears to out-perform the basic method of Windham and Cutler (1992), and to be equivalent to the bootstrap likelihood ratio method for large sample sizes.

Suggested Citation

  • Polymenis, A. & Titterington, D. M., 1998. "On the determination of the number of components in a mixture," Statistics & Probability Letters, Elsevier, vol. 38(4), pages 295-298, July.
  • Handle: RePEc:eee:stapro:v:38:y:1998:i:4:p:295-298
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    References listed on IDEAS

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    1. G. J. McLachlan, 1987. "On Bootstrapping the Likelihood Ratio Test Statistic for the Number of Components in a Normal Mixture," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(3), pages 318-324, November.
    2. Sylvia. Richardson & Peter J. Green, 1997. "On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(4), pages 731-792.
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    Cited by:

    1. Polymenis, Athanase, 2014. "A combined likelihood ratio/information ratio bootstrap technique for estimating the number of components in finite mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 107-115.
    2. A. Mooney, Jennifer & Helms, Peter J. & Jolliffe, Ian T., 2003. "Fitting mixtures of von Mises distributions: a case study involving sudden infant death syndrome," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 505-513, January.
    3. Najla M. Qarmalah & Jochen Einbeck & Frank P. A. Coolen, 2018. "k-Boxplots for mixture data," Statistical Papers, Springer, vol. 59(2), pages 513-528, June.

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