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)
This paper analyzes the power divergence estimators when homogeneity/heterogeneity hypotheses among standardized mortality ratios (SMRs) are taken into account. A Monte Carlo study shows that when the standard mortality rate is not external, that is it is estimated from the sample data, these estimators have a good performance even for small sample sets and(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)