Statistical Inference The Minimum Distance Approach

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 adju...

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Hlavní autori: Basu, Ayanendranath, Shioya, Hiroyuki, Park, Chanseok
Médium: E-kniha Kniha
Jazyk:English
Vydavateľské údaje: Boca Raton Chapman and Hall/CRC 2011
CRC Press, Taylor & Francis Group
CRC Press LLC
Chapman & Hall
CRC Press
Vydanie:1
Edícia:Chapman & Hall/CRC Monographs on Statistics and Applied Probability
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ISBN:9781420099652, 1420099655
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Popis
Shrnutí: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.
Bibliografia:Includes bibliographical references (p. 373-402) and index
ISBN:9781420099652
1420099655
DOI:10.1201/b10956