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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.
List of contents
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 Mardia's 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 Moments Estimation.- Computational Geometry and Statistical Depth Measures.- Partial Mixture Estimation and Outlier Detection in Data andRegression.- Robust Fitting Using Mean Shift: Applications in Computer Vision.- Testing the Equality of Location Parameters for Skewed Distributions Using S1 with High Breakdown Robust Scale Estimators.- Rank Scores Tests of Multivariate Independence.- The Influence of a Stochastic Interest Rate on the n-fold Compound Option.- Robust Estimations for Multivariate Sinh-1-Normal Distribution.- A Robust Estimator of the Tail Index Based on an Exponential Regression Model.- Robust Processing of Mechanical Vibration Measurements.- Quadratic Mixed Integer Programming Models in Minimax Robust Regression Estimators.
Summary
This book contains recent contributions to the theory and applications of robust statistics, presented at the International Conference on Robust Statistics (ICORS 2003) in Antwerp, Belgium. The papers deal with various aspects of robustness, including algorithms, asymptotics, inference and diagnostics. Many contributions contain links to other fields, such as computer vision, computational geometry, chemometrics and finance. Intended for both researchers and practitioners, this book will be a valuable resource for studying and applying recent robust statistical methods.
