Minimum Φ-divergence Estimator and Hierarchical Testing in Loglinear Models

نویسندگان

  • Noel Cressie
  • Leandro Pardo
  • LEANDRO PARDO
چکیده

In this paper we consider inference based on very general divergence measures, under assumptions of multinomial sampling and loglinear models. We define the minimum φ-divergence estimator, which is seen to be a generalization of the maximum likelihood estimator. This estimator is then used in a φ-divergence goodness-of-fit statistic, which is the basis of two new statistics for solving the problem of testing a nested sequence of loglinear models.

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تاریخ انتشار 2003