Ayanendranath Basu, Hiroyuki Shioya, Chanseok Park

Statistical Inference (eBook, PDF)

The Minimum Distance Approach

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 429
• Erscheinungstermin: 22. Juni 2011
• Englisch
• ISBN-13: 9781420099669
• Artikelnr.: 38295792

Autorenporträt

Ayanendranath Basu, Hiroyuki Shioya, Chanseok Park

Inhaltsangabe

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.