Minimum Φ-Divergence Estimator and Φ-Divergence Statistics in Generalized Linear Models with Binary Data

J. A. Pardo () and M. C. Pardo ()
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J. A. Pardo: Complutense University of Madrid
M. C. Pardo: Complutense University of Madrid

Methodology and Computing in Applied Probability, 2008, vol. 10, issue 3, 357-379

Abstract: Abstract In this paper, we assume that the data are distributed according to a binomial distribution whose probabilities follow a generalized linear model. To fit the data the minimum φ-divergence estimator is studied as a generalization of the maximum likelihood estimator. We use the minimum φ-divergence estimator, which is the basis of some new statistics, for solving the problems of testing in a generalized linear model with binary data. A wide simulation study is carried out for studying the behavior of the new family of estimators as well as of the new family of test statistics.

Keywords: Generalized linear model; Chi-squared distribution; Binomial distribution; φ-divergence measure; Nested sequence; 62B10; 62J12 (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1007/s11009-007-9054-2

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