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Maximum Trimmed Likelihood Estimator for Categorical Data Analysis

범주형 자료분석을 위한 최대절사우도추정

  • Choi, Hyun-Jip (Dept. of Applied Information Statistics, Kyonggi Univ.)
  • 최현집 (경기대학교 응용정보통계학과)
  • Published : 2009.03.30

Abstract

We propose a simple algorithm for obtaining MTL(maximum trimmed likelihood) estimates. The algorithm finds the subset to use to obtain the global maximum in the series of eliminating process which depends on the likelihood of cells in a contingency table. To evaluate the performance of the algorithm for MTL estimators, we conducted simulation studies. The results showed that the algorithm is very competitive in terms of computational burdens required to get the same or the similar results in comparison with the complete enumeration.

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