Theory and Applications of Recent Robust Methods [Hardcover]

Intended for both researchers and practitioners, this book will be a valuable resource for studying and applying recent robust statistical methods. It contains up-to-date research results in the theory of robust statistics

Treats computational aspects and algorithms and shows interesting and new applications.

Bias Behavior of the Minimum Volume Ellipsoid Estimate.- A Study of Belgian Inflation, Relative Prices and Nominal Rigidities using New Robust Measures of Skewness and Tail Weight.- Robust Strategies for Quantitative Investment Management.- An Adaptive Algorithm for Quantile Regression.- On Properties of Support Vector Machines for Pattern Recognition in Finite Samples.- Smoothed Local L-Estimation With an Application.- Fast Algorithms for Computing High Breakdown Covariance Matrices with Missing Data.- Generalized d-fullness Technique for Breakdown Point Study of the Trimmed Likelihood Estimator with Application.- On Robustness to Outliers of Parametric L2 Estimate Criterion in the Case of Bivariate Normal Mixtures: a Simulation Study.- Robust PCR and Robust PLSR: a Comparative Study.- Analytic Estimator Densities for Common Parameters under Misspecified Models.- Empirical Comparison of the Classification Performance of Robust Linear and Quadratic Discriminant Analysis.- Estimates of the Tail Index Based on Nonparametric Tests.- On Mardias Tests of Multinormality.- Robustness in Sequential Discrimination of Markov Chains under Contamination.- Robust Box-Cox Transformations for Simple Regression.- Consistency of the Least Weighted Squares Regression Estimator.- Algorithms for Robust Model Selection in Linear Regression.- Analyzing the Number of Samples Required for an Approximate Monte-Carlo LMS Line Estimator.- Visualizing 1D Regression.- Robust Redundancy Analysis by Alternating Regression.- Robust ML-estimation of the Transmitter Location.- A Family of Scale Estimators by Means of Trimming.- Robust Efficient Method of Mlóâ