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Add to basketGebundene Ausgabe. Condition: Sehr gut. Gebraucht - Sehr gut SG - Ungelesenes Mängelexemplar, gestempelt, mit leichten Lagerspuren - 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.
Published by Springer International Publishing, 2018
ISBN 10: 3319941526 ISBN 13: 9783319941523
Language: English
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Add to basketGebundene Ausgabe. Condition: Sehr gut. Gebraucht - Sehr gut SG - leichte Beschädigungen oder Verschmutzungen, ungelesenes Mängelexemplar, gestempelt - 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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