New families of estimators and test statistics in log-linear models |
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Authors: | Nirian Martín Leandro Pardo |
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Institution: | a Department of Statistics and O. R. III, School of Statistics, Complutense University of Madrid, 28040 Madrid, Spain b Department of Statistics and O. R. I, Faculty of Mathematics, Complutense University of Madrid, 28040 Madrid, Spain |
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Abstract: | In this paper we consider categorical data that are distributed according to a multinomial, product-multinomial or Poisson distribution whose expected values follow a log-linear model and we study the inference problem of hypothesis testing in a log-linear model setting. The family of test statistics considered is based on the family of ?-divergence measures. The unknown parameters in the log-linear model under consideration are also estimated using ?-divergence measures: Minimum ?-divergence estimators. A simulation study is included to find test statistics that offer an attractive alternative to the Pearson chi-square and likelihood-ratio test statistics. |
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Keywords: | 62H17 |
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