Springer Series in the Data Sciences

A Parametric Approach to Nonparametric Statistics

Authors: Alvo, Mayer, Yu, Philip

  • Includes exercises at the end of every chapter
  • First book to bridge the gap between parametric and nonparametric statistics
  • Contains introduction to probability and statistics
  • Demonstrates Modern applications
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Buy this book

eBook  
  • ISBN 978-3-319-94153-0
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover ca. 62,39 €
price for Spain (gross)
  • Due: September 2, 2018
  • ISBN 978-3-319-94152-3
  • Free shipping for individuals worldwide
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this Textbook

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.

About the authors

Mayer Alvo is a Professor in the Department of Mathematics and Statistics at the University of Ottawa. He received his Ph.D. from Columbia University in 1972. He served as Departmental Chairman in 1985-88, 2002- 2005 and 2011-2012. He is the author of more than 64 articles published in refereed journals. His research interests include nonparametric statistics, Bayesian analysis and sequential methods. 
Philip L.H. Yu is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Hong Kong. He received his Ph.D. from The University of Hong Kong in 1993. He is the Director of the Master of Statistics Programme. He is an Associate Editor for Computational Statistics and Data Analysis as well as for Computational Statistics. He is the author of more than 90 referred publications.  His research interests include modeling of ranking data, data mining and financial and risk analytics.

Buy this book

eBook  
  • ISBN 978-3-319-94153-0
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover ca. 62,39 €
price for Spain (gross)
  • Due: September 2, 2018
  • ISBN 978-3-319-94152-3
  • Free shipping for individuals worldwide
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
A Parametric Approach to Nonparametric Statistics
Authors
Series Title
Springer Series in the Data Sciences
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG, part of Springer Nature
eBook ISBN
978-3-319-94153-0
DOI
10.1007/978-3-319-94153-0
Hardcover ISBN
978-3-319-94152-3
Series ISSN
2365-5674
Edition Number
1
Number of Pages
IV, 268
Number of Illustrations and Tables
5 b/w illustrations
Topics