Robustness in Data Analysis: Criteria and Methods: 6 (Modern Probability & Statistics) - Tapa dura

Shevlyakov, Georgy L.; Vilchevski, Nikita O.

 
9789067643511: Robustness in Data Analysis: Criteria and Methods: 6 (Modern Probability & Statistics)
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ISBN 10: 9067643513 ISBN 13: 9789067643511
Editorial: De Gruyter, 2001

Sinopsis

The series is devoted to the publication of high-level monographs and surveys which cover the whole spectrum of probability and statistics. The books of the series are addressed to both experts and advanced students.

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Reseña del editor

01/07 This title is now available from Walter de Gruyter. Please see www.degruyter.com for more information. The field of mathematical statistics called robustness statistics deals with the stability of statistical inference under variations of accepted distribution models. Although robust statistics involves mathematically highly defined tools, robust methods exhibit a satisfactory behaviour in small samples, thus being quite useful in applications. This volume in the book series Modern Probability and Statistics addresses various topics in the field of robust statistics and data analysis, such as: a probability-free approach in data analysis; minimax variance estimators of location, scale, regression, autoregression and correlation; L1-norm methods; adaptive, data reduction, bivariate boxplot, and multivariate outlier detection algorithms; applications in reliability, detection of signals, and analysis of the sudden cardiac death risk factors. The book contains new results related to robustness and data analysis technologies, including both theoretical aspects and practical needs of data processing, which have been relatively inaccessible as they were originally only published in Russian. This book will be of value and interest to researchers in mathematical statistics as well as to those using statistical methods.

Reseña del editor

The field of mathematical statistics called robustness statistics deals with the stability of statistical inference under variations of accepted distribution models. Although robustness statistics involves mathematically highly defined tools, robust methods exhibit a satisfactory behaviour in small samples, thus being quite useful in applications. This volume addresses various topics in the field of robust statistics and data analysis, such as: a probability-free approach in data analysis; minimax variance estimators of location, scale, regression, autoregression and correlation; L1-norm methods; adaptive, data reduction, bivariate boxplot, and multivariate outlier detection algorithms; applications in reliability, detection of signals, and analysis of the sudden cardiac death risk factors. The text contains results related to robustness and data analysis technologies, including both theoretical aspects and practical needs of data processing.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
De Gruyter
Año de publicación
2001
Idioma
Inglés
ISBN 10 
9067643513
ISBN 13 
9789067643511
Encuadernación
Tapa dura
Número de páginas
326
Contacto del fabricante
no disponible
Persona responsable
no disponible

Otras ediciones populares con el mismo título

9783111828831: Robustness in Data Analysis: Criteria and Methods (Modern Probability and Statistics)

Edición Destacada

ISBN 10:  3111828832 ISBN 13:  9783111828831
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