Overview
- Offers an up-to-date review of of the theory of multivariate
- nonparametric methods based on spatial signs and ranks
- Provides concise and self-contained treatment of the theory
- Examples accompanied by a free R package called MNM allows for
- immediate experimentation of the procedures
Part of the book series: Lecture Notes in Statistics (LNS)
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Table of contents (14 chapters)
Keywords
About this book
Reviews
From the reviews:
“This monograph, part of the Lecture Notes in Statistics series, provides a complete overview of multivariate analysis methods based on spatial signs and ranks. It covers a wide range of topics in classical multivariate analysis and presents some deep theoretical results. … It may serve as ‘a general reference for the latest developments in the area.’ … In summary, Multivariate Nonparametric Methods With R is a good reference book for the area of multivariate nonparametric methods based on spatial signs and ranks … .” (Gang Shen, Journal of the American Statistical Association, Vol. 106 (496), December, 2011)
“This book provides an overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. … In most chapters, the theory and methods are illustrated with examples. Furthermore, the R package MNM is available for computation of the procedures, and the code for the analysis of example data set is also provided in the text.” (Elvan Ceyhan, Mathematical Reviews, Issue 2011 g)
Authors and Affiliations
Bibliographic Information
Book Title: Multivariate Nonparametric Methods with R
Book Subtitle: An approach based on spatial signs and ranks
Authors: Hannu Oja
Series Title: Lecture Notes in Statistics
DOI: https://doi.org/10.1007/978-1-4419-0468-3
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2010
Softcover ISBN: 978-1-4419-0467-6Published: 09 April 2010
eBook ISBN: 978-1-4419-0468-3Published: 25 March 2010
Series ISSN: 0930-0325
Series E-ISSN: 2197-7186
Edition Number: 1
Number of Pages: XIV, 234
Topics: Probability Theory and Stochastic Processes, Econometrics, Simulation and Modeling, Statistical Theory and Methods, Biometrics, Statistics for Life Sciences, Medicine, Health Sciences