Simplified maximum likelihood inference based on the likelihood decomposition for missing data

Sangah Jung, Sangun Park

Research output: Contribution to journalArticle


Summary: In this paper, we propose an estimation method when sample data are incomplete. We decompose the likelihood according to missing patterns and combine the estimators based on each likelihood weighting by the Fisher information ratio. This approach provides a simple way of estimating parameters, especially for non-monotone missing data. Numerical examples are presented to illustrate this method.

Original languageEnglish
Pages (from-to)271-283
Number of pages13
JournalAustralian and New Zealand Journal of Statistics
Issue number3
Publication statusPublished - 2013 Sep 1


All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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