AISM 52, 481-487
(Received December 1, 1997; revised April 5, 1999)
Abstract. We show that iterative methods for maximizing the likelihood in a mixture of exponentials model depend strongly on their particular implementation. Different starting strategies and stopping rules yield completely different estimators of the parameters. This is demonstrated for the likelihood ratio test of homogeneity against two-component exponential mixtures, when the test statistic is calculated by the EM algorithm.
Key words and phrases: EM algorithm, exponential mixture models, initial values, stopping criteria, maximum likelihood estimation, likelihood ratio test.
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