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Developments in Robust Statistics R Developments in Robust Statistics R. Dutter . P. Filzmoser u. Gather . P. 1. Rousseeuw Editors Developments in Robust Statistics International Conference on Robust Statistics 2001 With 85 Figures and 75 Tables Springer-Verlag Berlin Heidelberg GmbH Professor Dr. Rudolf Dutter Professor Dr. Peter Filzmoser Vienna University of Technology Institute of Statistics Wiedner HauptstraBe 8-10 1040 Vienna, Austria Professor Dr. Ursula Gather University of Dortmund Statistics Department 44221 Dortmund, Germany Professor Dr. Peter J. Rousseeuw University of Antwerp Department of Mathematics and Computer Science Universiteitsplein 1 2610 Antwerp, Belgium ISBN 978-3-642-63241-9 ISBN 978-3-642-57338-5 (eBook) DOI 10.1007/978-3-642-57338-5 Library of Congress Cataloging·in·Publication Data applied for Developments in Robust Statistics / International Conference on Robust Statistics 2ool. Ed.: Rudolf Dutter. ... - Heidelberg; New York: Physica-Verl., 2003 This work is subject to copyright. Ali rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Physica-Verlag. Violations are liable for prosecution under the German Copyright Law. http://www.springer.de © Springer-Verlag Berlin Heidelberg 2003 Originally published by Physica-Verlag Heidelberg 2003 The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: Erich Kirchner, Heidelberg SPIN 10886288 88/2202-5 4 3 2 1 0- Printed on acid-free paper Preface This book contains papers that were presented at the International Conference on Robust Statistics 2001 (ICORS 2001), held from July 23-27, 2001 in Vorau, Aus­ tria. The objective of this conference was to be a forum for new developments and applications of Robust Statistics. Leading scientists, experienced researchers and practitioners, as well as younger researchers came together to exchange knowledge and to build scientific contacts. Many excellent meetings on robustness have been organized in the past, but there was no periodical meeting to bring together researchers working in this field, to exchange knowledge and to discuss future directions of the discipline. To fill this need, Peter Filzmoser and Rodolf Dutter from the Vienna University ofTechnology organized ICORS 2001, a conference especially devoted to robust statistics. The conference site Vorau, unknown even to many Austrian people, turned out to be a very successful venue for this event. About 100 participants from 25 nations attended this meeting. The scien­ tific program included 67 oral and 13 poster presentations. This program had been prepared by the Scientific Committee consisting of Rudolf Dutter (Aus­ tria, chair), Christophe Croux (Belgium), llikan Ekblom (Sweden), Luisa Fern­ holz (USA), Ursula Gather (Germany), Marc Genton (USA), Xurning He (USA), Thomas Hettmansperger (USA), Yurij Kharin (Belarus), Ricardo Maronna (Ar­ gentina), Douglas Martin (USA), Stephan Morgenthaler (Switzerland), Christine Miiller (Germany), Hannu Oja (Finland), David Rocke (USA), Elvezio Ronchetti (Switzerland), Peter Rousseeuw (Belgium), Charles Stewart (USA), Victor Yohai (Argentina), and Ruben Zamar (Canada). Aspects of Robust Statistics were cov­ ered in the following areas: Algorithms, Applications, Biostatistics, Computing and graphics, Data analysis, Data mining, Economics and finance, Efficiency and ro­ bustness, Functionals and bias, Fuzzy statistics, Geostatistics, Inference for robust methods and model testing, Location depth and regression depth, Multivariate meth­ ods, Neural networks, Rank-based methods, Regression quantiles and trimming, Ro­ bust covariance, Robust designs, Robust regression, Time series analysis, Wavelets. All papers in this volume have been refereed by the Scientific Committee and by anonymous referees, and we would like to express our sincere gratitude to all of them. The list ofreferees is given at the end of the volume. Twelve papers presented at the conference are reprinted from the journal Metrika (Springer-Verlag), Vol. 55, VI Preface Issue 1-2, 2002. Throughout this volume, the style has been unified as much as possible. The conference was mainly sponsored by the European Commission (Human Potential Programme, High-Level Scientific Conferences). This program especially supported young researchers from European member states, and this led to a high number of young scientists at the conference. The papers in this book consider the following subjects of robust statistics. A fundamental problem of data summary, called Weights ofEvidence, is considered by Morgenthaler and Staudte and its robustness properties are studied. Further the­ oretical papers may be partially ordered by keywords: Scale: H.L. Koul. Skewness: G. Brys, M. Hubert, and A Struyf. Content-corrected tolerance limits: L.T. Fern­ holz. Quantile regression: D. Tasche. Generalized linear models: N.M. Neykov and C.H. Miiller. Linear structural relation model: M.M. Souto de Miranda. Nonpara­ metric regression: A. Kovac; C.H. Miiller. Time series: C. Agostinelli; Y. Kharin. Longitudinal data: E. Cantoni; X. He and M.-O. Kim. Finance: GJ. Lauprete, A.M. Samarov, and R.E. Welsch. Space/time: M.G. Genton. Multivariate methods: M. Hubert, PJ. Rousseeuw, and S. Verboven; G.A Koshevoy; M.R. Oliveira and lA Branco. Tests: T. Bednarski; A.a. Onder and A Zaman; A Peters and P. Sib­ bertsen; G. Willems, G. Pison, P.J. Rousseeuw, and S. Van Aelst. Computational aspects and algorithms are considered by the following au­ thors: J. Agu1l6; J. Antoch and H. Ekblom; O. Arslan; O. Arslan, O. Edlund, and H. Ekblom; S. Langerman and W. Steiger; AM. Pires; G. Pison, S. Van Aelst and G. Willems; T. Ronkainen, H. Oja, and P. Orponen. Applied papers were written by: G.w. Bassett Jr., M.-Y.S. Tam, and K. Knight; R.Y. Liu; AJ. Stromberg, W. Griffith, and M. Smith. Programming tools are dis­ cussed by: C. Chen; V. Todorov. RudolfDutter Peter Filzmoser Ursula Gather Peter J. Rousseeuw Table of Contents Preface. 0 ••• 0 •••• 0 ••••••••• 0 •••••• 0 •••••••••• 00 ••• 0 •••••• 0..... V List ofParticipants 0 0 ••••••• 0 •• 0 •••• 0 ••••••• 0 0 ••• 0 ••• 0 0 •• 0 •••• 0 0 0 XI List of Referees . 0 • 0 ••••••••••• 0 ••••••••••• 0 •••• 0 •••• 0 ••••• 0 • 0 • • • XV Robust Time Series Estimation via Weighted Likelihood C. Agostinelli .. 0 0 0 ••••• 0 0 • 0 • 0 0 •• 0 0 0 •••• 0 0 • 0 •• 0 0 ••• 0 •••• 0 •• 0 •••• 0 1 An Exchange Algorithm for Computing the Least Quartile Difference Estimator J. Aguila ... 0 ••••••• 0 •• 0 •• 0 ••••••••••••• 0 • 0 ••• 0 ••••• 0 0 •••••••• o. 17 Selected Algorithms for Robust M- and L-Regression Estimators 1. Antoch and Ho Ekblom . 0 0 •••• 0 •• 0 •• 0 •••• 0 ••••••••••• 0 ••••• 0 • • • •• 32 A Simple Test to Identify Good Solutions of Redescending M Estimating Equations for Regression O. Arslan .... 0 0 •• 0 0 0 • 0 0 •••••• 0 •• 0 •• 0 0 • 0 0 0 •••••• 0000•00•00•0 •••• 0 50 Algorithms to Compute CM- and S-Estimates for Regression 00 Arslan, 0. Edlund, and H. Ekblom .... 0 •• 0 •••••• 0 0 0 0 0 • 0 0 ••• 0 • 0 0 • •• 62 Quantile Models and Estimators for Data Analysis Go\¥. Bassett Jr., M.-Y.S. Tam, and K. Knight . 0 0 0 •••• 0 ••••••••••••• 0 0 o. 77 Estimation in the Generalized Poisson Model via Robust Testing T. Bednarski ..... 0 ••••• 0 ••• 0 • 0 ••••••••••••••• 0 •• 0 0 •• 0 ••• 0 0 ••• 0 •• 88 A Comparison of Some New Measures of Skewness G. Brys, M. Hubert, and A. Struyf .. 0 •••••• 0 •••••• 0 •• 0 •••••••• 0 0 ••• o. 98 Robust Inference Based on Quasi-likelihoods for Generalized Linear Models and Longitudinal Data Eo Cantoni . 0 • 0 ••••••••• 0 •• 0 0 0 • 0 •• 0 0 •• 0 ••••• 0 0 ••••• 0 •••••• 0 •••• o' 114 Robust Tools in SAS Co Chen ... 0 •••••••••••• 0 ••••• 0 •••• 0 •••••••• 00 •• 0.000 •• 0.0 •• 0.0. 125 VIII Table of Contents Robustness Issues Regarding Content-corrected Tolerance Limits L. T. Fernholz 134 Breakdown-point for Spatially and Temporally Correlated Observations M.G. Genton 148 On Marginal Estimation in a Semiparametric Model for Longitudinal Data with Time-independent Covariates X. He and M.-O. Kim 160 Robust PCA for High-dimensional Data M. Hubert, P.l. Rousseeuw, and S. Verboven 169 Robustness Analysis in Forecasting ofTime Series Y. Kharin ..................................................... .. 180 Lift-zonoid and Multivariate Depths G.A. Koshevoy ................................................. .. 194 Asymptotic Distributions of Some Scale Estimators in Nonlinear Models H.L. Koul 203 Robust Nonparametric Regression and Modality A. Kovac 218 Computing a High Depth Point in the Plane S. Langerman and w: Steiger 228 Robust Portfolio Optimization G.J. Lauprete, A.M. Samarov, and R.E. Welsch 235 BootQC: Bootstrap for Robust Analysis of Aviation Safety Data R. Y. Liu 246 Optimal Weights of Evidence with Bounded Influence S. Morgenthaler and R. Staudte 259 Robust Estimators for Estimating Discontinuous Functions C.H. Muller 266 Breakdown Point and Computation ofTrimmed Likelihood Estimators in Generalized Linear Models N.M. Neykov and CH. Muller
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