Robustness in Data Analysis: Criteria and Methods (Modern Probability & Statistics Reprint 2012)

Robustness in Data Analysis: Criteria and Methods (Modern Probability & Statistics Reprint 2012)

By: Nikita O. Vilchevski (author), Georgy L. Shevlyakov (author)Hardback

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Description

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.

Contents

General remarks; Huber minimax approach; Hampel approach; optimization criteria in data analysis - a probability-free approach; introductory remarks; translation and scale equivariant contrast functions; orthogonal equivariant contrast functions; monotonically equivariant contrast functions; minimal sensitivity to small perturbations in the data; affine equivariate contrast functions; robust mimimax estimation of location; introductory remarks; robust estimation of location in models with bounded variances; robust estimation of location in models with bounded subranges; robust estimators of multivariate location; least informative lattice distributions; robust estimation of scale; introductory remarks; measures of scale defined by functionals; M-, L-, and R-estimators of scale; Huber minimax estimator of scale; final remarks; robust regression and autoregression; introductory remarks; the minimax variance regression; robust autoregression; robust identification in dynamic models; final remarks; robustness of L1-norm estimators; introductory remarks; stability of L1-approximations; robustness of the L1-regression; final remarks; robust estimation of correlation; introductory remarks; analysis - Monte Carlo experiment; analysis - asymptotic characteristics; synthesis; minimax variance correlation; two-stage estimators - rejection of outliers plus classics; computation and data analysis technologies; introductory remarks on computation; adaptive robust procedures; smoothing quantile functions by the Bernstein polynomials; robust bivariate boxplots; applications; on robust elimination in the statistical theory of reliability; robust detection of signals based on optimisation criteria; statistical analysis of sudden cardiac death risk factors.

Product Details

  • ISBN13: 9789067643511
  • Format: Hardback
  • Number Of Pages: 318
  • ID: 9789067643511
  • weight: 650
  • ISBN10: 9067643513
  • edition: Reprint 2012

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