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Zusatztext "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 Informationen zum Autor Ayanendranath Basu, Hiroyuki Shioya, Chanseok Park Klappentext This book gives a comprehensive account of density-based minimum distance methods and their use in statistical inference. It covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, graphical descriptions of robustness, penalized and combined distances, multisample methods, weighted likelihood, and multinomial goodness-of-fit tests. The book also introduces the minimum distance methodology in interdisciplinary areas, such as neural networks and image processing, as well as specialized models and problems, including regression, mixture models, survival and Bayesian analysis, and more. Zusammenfassung Presents an account of density-based minimum distance methods and their use in statistical inference. This book covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, and graphical descriptions of robustness. Inhaltsverzeichnis 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. ...
