Non-parametric log-concave mixtures

  • Authors:

  • Paul H. C. Eilers;M. W. Borgdorff

  • Affiliations:

  • Department of Medical Statistics, Leiden University Medical Centre, P.O. Box 9604, 2300 RC Leiden, The Netherlands;Royal Netherlands Tuberculosis Association (KNCV), The Hague, The Netherlands

  • Venue:
  • Computational Statistics & Data Analysis
  • Year:
  • 2007

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Abstract

Finite mixtures of parametric distributions are often used to model data of which it is known or suspected that there are sub-populations. Instead of a parametric model, a penalized likelihood smoothing algorithm is developed. The penalty is chosen to favor a log-concave result. The standard EM algorithm (''split and fit'') can be used. Theoretical results and applications are presented.