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

Abstract

In this paper the family of phi-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.