大葉大學圖書館 |

Methodology in robust and nonparametric statistics[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	519.5
書名/作者:	Methodology in robust and nonparametric statistics/ Jana Jurečková, Pranab Kumar Sen, Jan Picek.
作者:	Jurečková, Jana,
其他作者:	Sen, Pranab Kumar,
出版者:	Boca Raton, FL : : CRC Press,, c2012.
面頁冊數:	1 online resource (xv, 384 p.)
標題:	Robust statistics.
標題:	Nonparametric statistics.
標題:	Statistics as Topic.
標題:	Statistics, Nonparametric.
ISBN:	9781439840696 (electronic bk.)
ISBN:	1439840695 (electronic bk.)
書目註:	Includes bibliographical references (p. 357-384).
內容註:	Preliminaries -- Robust estimation of location and regression -- Asymptotic representations for L-estimators -- Asymptotic representations for M-estimators -- Asymptotic representations for R-estimators -- Asmptotic interralations of estimators -- Robust estimation: multivariate perspectives -- Robust tests and confidence sets.
摘要、提要註:	"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.
電子資源:	http://www.crcnetbase.com/isbn/9781439840696

Methodology in robust and nonparametric statistics[electronic resource] /
Jurečková, Jana,1940-

Methodology in robust and nonparametric statistics[electronic resource] /Jana Jurečková, Pranab Kumar Sen, Jan Picek. - Boca Raton, FL :CRC Press,c2012. - 1 online resource (xv, 384 p.)

Includes bibliographical references (p. 357-384).

Preliminaries -- Robust estimation of location and regression -- Asymptotic representations for L-estimators -- Asymptotic representations for M-estimators -- Asymptotic representations for R-estimators -- Asmptotic interralations of estimators -- Robust estimation: multivariate perspectives -- 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.

ISBN: 9781439840696 (electronic bk.)Subjects--Topical Terms:

446882
Robust statistics.
Index Terms--Genre/Form:

336502
Electronic books.

LC Class. No.: QA276

Dewey Class. No.: 519.5

National Library of Medicine Call No.: QA 276

Methodology in robust and nonparametric statistics[electronic resource] /
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245 1 0 $a Methodology in robust and nonparametric statistics $h [electronic resource] / $c Jana Jurečková, Pranab Kumar Sen, Jan Picek.
260 $a Boca Raton, FL : $b CRC Press, $c c2012.
300 $a 1 online resource (xv, 384 p.)
504 $a Includes bibliographical references (p. 357-384).
505 0 $a Preliminaries -- Robust estimation of location and regression -- Asymptotic representations for L-estimators -- Asymptotic representations for M-estimators -- Asymptotic representations for R-estimators -- Asmptotic interralations of estimators -- Robust estimation: multivariate perspectives -- Robust tests and confidence sets.
520 $a "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.
588 0 $a Print version record.
650 0 $a Robust statistics. $3 446882
650 0 $a Nonparametric statistics. $3 405341
650 2 $a Statistics as Topic. $3 515555
650 2 $a Statistics, Nonparametric. $3 609153
655 0 $a Electronic books. $2 local $3 336502
700 1 $a Sen, Pranab Kumar, $d 1937- $3 609151
700 1 $a Picek, Jan. $3 609152
856 4 0 $u http://www.crcnetbase.com/isbn/9781439840696