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About this product
- DescriptionThe 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-rm 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 techlogies, including both theoretical aspects and practical needs of data processing.
- Author(s)Georgy L. Shevlyakov,Nikita O. Vilchevski
- Date of Publication20/02/2001
- Series TitleModern Probability & Statistics
- Series Part/Volume Number6
- Place of PublicationZeist
- Country of PublicationNetherlands
- ImprintVSP International Science Publishers
- Content NoteNum. figs.
- Weight650 g
- Width165 mm
- Height249 mm
- Spine22 mm
- Interest AgeCollege Graduate Student
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