Publication: Minimum power-divergence estimator in three-way contingency tables
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Publication Date
2003
Authors
Pardo Llorente, MarĂa del Carmen
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Tailor and Francis
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Abstract
Cressie et al. (2000; 2003) introduced and studied a new family of statistics, based on the phi-divergence measure, for solving the problem of testing a nested sequence of loglinear models. In that family of test statistics the parameters are estimated using the minimum phi-divergence estimator which is a generalization of the maximum likelihood estimator. In this paper we study the minimum power-divergence estimator (the most important family of minimum phi-divergence estimator) for a nested sequence of loglinear models in three-way contingency tables under assumptions of multinomial sampling. A simulation study illustrates that the minimum chi-squared estimator is simultaneously the most robust and efficient estimator among the family of the minimum power-divergence estimator.