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Robustness in Data Analysis: Criteria and Methods (Modern Probability and Statistics, 6) [Hardcover]

Robustness in Data Analysis: Criteria and Methods (Modern Probability and Statistics, 6) [Hardcover]

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Item description for Robustness in Data Analysis: Criteria and Methods (Modern Probability and Statistics, 6) by Georgy L. Shevlyakov & Nikita O. Vilchevski...

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.



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Item Specifications...


Studio: Walter de Gruyter
Pages   310
Est. Packaging Dimensions:   Length: 9.61" Width: 6.46" Height: 0.87"
Weight:   1.54 lbs.
Binding  Hardcover
Publisher   Walter de Gruyter Inc
ISBN  9067643513  
ISBN13  9789067643511  


Availability  126 units.
Availability accurate as of Jan 17, 2017 02:33.
Usually ships within one to two business days from La Vergne, TN.
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More About Georgy L. Shevlyakov & Nikita O. Vilchevski


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Product Categories

1Books > Subjects > Professional & Technical > Professional Science > Mathematics > Applied > Statistics
2Books > Subjects > Science > General
3Books > Subjects > Science > Mathematics > Applied > Probability & Statistics



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