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Minimum phi-divergence estimators for loglinear models with linear constraints and multinomial sampling

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Abstract

In this paper the family ofφ-divergence estimators for loglinear models with linear constraints and multinomial sampling is studied. This family is an extension of the maximum likelihood estimator studied by Haber and Brown (1986). A simulation study is presented and some alternative estimators to the maximum likelihood are obtained.

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Authors and Affiliations

  1. Escuela Universitaria de Estadística, Universidad Complutense de Madrid, Spain

    N. Martín

  2. Facultad de Matemáticas, Universidad Complutense de Madrid, Spain

    L. Pardo

Authors
  1. N. Martín
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  2. L. Pardo
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Additional information

This work was parcially supported by Grant DGES PB2003-892

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Martín, N., Pardo, L. Minimum phi-divergence estimators for loglinear models with linear constraints and multinomial sampling. Statistical Papers 49, 15–36 (2008). https://doi.org/10.1007/s00362-006-0370-3

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  • DOI: https://doi.org/10.1007/s00362-006-0370-3

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