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A Parametric Approach to Nonparametric Statistics

A Parametric Approach to Nonparametric Statistics

Mayer Alvo / Philip L. H. Yu

78,30 €
IVA incluido
Disponible
Editorial:
Springer Nature B.V.
Año de edición:
2018
Materia
Probabilidad y estadística
ISBN:
9783030068042
78,30 €
IVA incluido
Disponible

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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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Otros libros del autor

  • Statistical Methods for Ranking Data
    Mayer Alvo / Philip L. H. Yu
    This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete...