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http://dx.doi.org/10.5351/CKSS.2012.19.1.135

An EM Algorithm for a Doubly Smoothed MLE in Normal Mixture Models  

Seo, Byung-Tae (Department of Statistics, Sungkyunkwan University)
Publication Information
Communications for Statistical Applications and Methods / v.19, no.1, 2012 , pp. 135-145 More about this Journal
Abstract
It is well known that the maximum likelihood estimator(MLE) in normal mixture models with unequal variances does not fall in the interior of the parameter space. Recently, a doubly smoothed maximum likelihood estimator(DS-MLE) (Seo and Lindsay, 2010) was proposed as a general alternative to the ordinary maximum likelihood estimator. Although this method gives a natural modification to the ordinary MLE, its computation is cumbersome due to intractable integrations. In this paper, we derive an EM algorithm for the DS-MLE under normal mixture models and propose a fast computational tool using a local quadratic approximation. The accuracy and speed of the proposed method is then presented via some numerical studies.
Keywords
EM algorithm; normal mixture; doubly-smoothed MLE; quadratic approximation;
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