A Parametric Approach to Nonparametric Statistics

Nonfiction, Science & Nature, Mathematics, Statistics
Cover of the book A Parametric Approach to Nonparametric Statistics by Mayer Alvo, Philip L. H. Yu, Springer International Publishing
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Author: Mayer Alvo, Philip L. H. Yu ISBN: 9783319941530
Publisher: Springer International Publishing Publication: October 12, 2018
Imprint: Springer Language: English
Author: Mayer Alvo, Philip L. H. Yu
ISBN: 9783319941530
Publisher: Springer International Publishing
Publication: October 12, 2018
Imprint: Springer
Language: English

This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make use of Bayesian methods to analyze ranking data. The book bridges the gap between parametric and nonparametric statistics and presents the best practices of the former while enjoying the robustness properties of the latter.

This book can be used in a graduate course in nonparametrics, with parts being accessible to senior undergraduates.  In addition, the book will be of wide interest to statisticians and researchers in applied fields.

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This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make use of Bayesian methods to analyze ranking data. The book bridges the gap between parametric and nonparametric statistics and presents the best practices of the former while enjoying the robustness properties of the latter.

This book can be used in a graduate course in nonparametrics, with parts being accessible to senior undergraduates.  In addition, the book will be of wide interest to statisticians and researchers in applied fields.

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