Methodology in Robust and Nonparametric Statistics - Softcover

Jureckova, Jana; Sen, Pranab; Picek, Jan

Softcover

ISBN 10: 0367381060 ISBN 13: 9780367381066

Publisher: Routledge, 2019

Synopsis

Robust and nonparametric statistical methods have their foundation in fields ranging from agricultural science to astronomy, from biomedical sciences to the public health disciplines, and, more recently, in genomics, bioinformatics, and financial statistics. These disciplines are presently nourished by data mining and high-level computer-based algorithms, but to work actively with robust and nonparametric procedures, practitioners need to understand their background.

Explaining the underpinnings of robust methods and recent theoretical developments, Methodology in Robust and Nonparametric Statistics provides a profound mathematically rigorous explanation of the methodology of robust and nonparametric statistical procedures.

Thoroughly up-to-date, this book

• Presents multivariate robust and nonparametric estimation with special emphasis on affine-equivariant procedures, followed by hypotheses testing and confidence sets



• Keeps mathematical abstractions at bay while remaining largely theoretical



• Provides a pool of basic mathematical tools used throughout the book in derivations of main results

The methodology presented, with due emphasis on asymptotics and interrelations, will pave the way for further developments on robust statistical procedures in more complex models. Using examples to illustrate the methods, the text highlights applications in the fields of biomedical science, bioinformatics, finance, and engineering. In addition, the authors provide exercises in the text.

About this title

About the Author

Jure?ková, Jana; Sen, Pranab; Picek, Jan

From the Back Cover

Closely related to nonparametric methods, robust statistical methods are not unduly affected by data outliers or other small departures from model assumptions. This book presents a comprehensive overview of methodology for robust and nonparametric statistics. It covers both methods in parallel to demonstrate their relative strengths and weaknesses. Using examples to illustrate the methods, the text emphasizes applications in the fields of biomedical science, bioinformatics, finance, and engineering. The authors provide exercises in the text.

Edition details

• Publisher: Routledge
• Publication date: 2019
• Language: English
• ISBN 10: 0367381060
• ISBN 13: 9780367381066
• Binding: Paperback
• Edition number: 1
• Number of pages: 410