Statistical Inference

Ayanendranath Basu, Hiroyuki Shioya, Chanseok Park

"The book is an excellent and thorough outline of work in the area. It would provide an ideal volume for someone who plans to undertake research in the area."—International Statistical Review, 2013"The book provides a comprehensive overview of the theory of density-based minimum distance methods and it is well written and easy to read and understand. The book is well suited for graduate students, professionals and researchers not only in statistics but also in biosciences, engineering and various other fields where statistical inference plays a fundamental role."—Alex Karagrigoriou, Journal of Applied Statistics, 2012

• Introduction. Statistical Distances. Continuous Models. Measures of Robustness and Computational Issues. The Hypothesis Testing Problem. Techniques for Inlier Modification. Weighted Likelihood Estimation. Multinomial Goodness-of-fit Testing. The Density Power Divergence. Other Applications. Distance Measures in Information and Engineering. Applications to Other Models.