Statistical Inference Based on Divergence Measures

Organized in systematic way, Statistical Inference Based on Divergence Measures presents classical problems of statistical inference, such as estimation and hypothesis testing, on the basis of measures of entropy and divergence with applications to multinomial and generation populations. On the basis of divergence measures, this book introduces minimum divergence estimators as well as divergence test statistics and compares them to the classical maximum likelihood estimator, chi-square test statistics, and the likelihood ratio test in different statistical problems. The text includes over 120 exercises with solutions, making it ideal for students with a basic knowledge of statistical methods.