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Название: Statistical Inference Based on Divergence Measures
Авторы: Pardo L., Llorente L.P.
Pardo (statistics and operations research, Complutense U. of Madrid, Spain) analyzes issues of statistical inference, such as estimation and hypotheses testing, using measures of entropy and divergence. He discusses Information Theory, asymptotic behavior of measure of entropy in solving statistical problems, statistical analysis of discrete multivariate data, goodness-of-fit in simple and composite null hypothesis, optimality of phi-divergence test statistics, minimum phi-divergence estimators, loglinear models, contingency tables, and testing in general populations.