EM estimation for finite mixture models with known mixture component size

Chen Teel, Taeyoung Park, Allan R. Sampson

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


We consider the use of an EM algorithm for fitting finite mixture models when mixture component size is known. This situation can occur in a number of settings, where individual membership is unknown but aggregate membership is known. When the mixture component size, i.e., the aggregate mixture component membership, is known, it is common practice to treat only the mixing probability as known. This approach does not, however, entirely account for the fact that the number of observations within each mixture component is known, which may result in artificially incorrect estimates of parameters. By fully capitalizing on the available information, the proposed EM algorithm shows robustness to the choice of starting values and exhibits numerically stable convergence properties.

Original languageEnglish
Pages (from-to)1545-1556
Number of pages12
JournalCommunications in Statistics: Simulation and Computation
Issue number6
Publication statusPublished - 2015 Jul 3

Bibliographical note

Funding Information:
This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2011-0011866) and the NIMH grant (1-P50-MH084053).

Publisher Copyright:
© 2015 Taylor & Francis Group, LLC.

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation


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