Learn More
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(More)
For data generated by stationary Markov chains there are considered estimates of chain parameters minimizing ^-divergences between theoretical and empirical distributions of states. Consistency and asymptotic normality are established and the asymptotic covari-ance matrices are evaluated. Testing of hypotheses about the stationary distributions based on(More)