Methodology in robust and nonparametric statistics / Jana Jure�ckov�a, Pranab Kumar Sen, Jan Picek.
Material type:
- 9781439840689
- Also available as an electronic resource.
Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|
Books | ISI Library, Kolkata | 000SA.13 J95 (Browse shelf(Opens below)) | Available | 136519 |
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000SA.12=4 R215 Statistique non parametric asymptotique | 000SA.13 D229 Robust response surfaces, regression, and positive data analyses / | 000SA.13 F221 Robust methods for data reduction / | 000SA.13 J95 Methodology in robust and nonparametric statistics / | 000SA.13 Sh554 Robust correlation : theory and applications / | 000SA.14 K64 Handbook of survival analysis / | 000SA.14 Z63 Empirical likelihood method in survival analysis / |
"A Chapman & Hall book."
Includes bibliographical references (p. 357-384) and indexes.
1. Introduction and synopsis -- 2. Preliminaries -- 3. Robust estimation of location and regression -- 4. Asymptotic representations for L-estimators -- 5. Asymptotic representations for M-estimators -- 6. Asymptotic representations for R-estimators -- 7. Asmptotic interrelations of estimators -- 8. Robust estimation : multivariate perspectives -- 9. Robust tests and confidence sets.
"Show 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"--Back cover.
Also available as an electronic resource.
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