Developments in Robust Statistics

International Conference on Robust Statistics 2001

  • Rudolf Dutter
  • Peter Filzmoser
  • Ursula Gather
  • Peter J. Rousseeuw

Table of contents

  1. Front Matter
    Pages I-XVI
  2. O. Arslan, O. Edlund, H. Ekblom
    Pages 62-76
  3. G. W. Bassett Jr., M. -Y. S. Tam, K. Knight
    Pages 77-87
  4. G. Brys, M. Hubert, A. Struyf
    Pages 98-113
  5. C. Chen
    Pages 125-133
  6. M. Hubert, P. J. Rousseeuw, S. Verboven
    Pages 169-179
  7. G. A. Koshevoy
    Pages 194-202
  8. S. Langerman, W. Steiger
    Pages 228-234
  9. G. J. Lauprete, A. M. Samarov, R. E. Welsch
    Pages 235-245
  10. S. Morgenthaler, R. Staudte
    Pages 259-265
  11. M. R. Oliveira, J. A. Branco
    Pages 287-295
  12. A. Ö. Önder, A. Zaman
    Pages 296-306
  13. G. Pison, S. Van Aelst, G. Willems
    Pages 330-343
  14. T. Ronkainen, H. Oja, P. Orponen
    Pages 344-359
  15. A. J. Stromberg, W. Griffith, M. Smith
    Pages 368-376
  16. S. Taskinen, A. Kankainen, H. Oja
    Pages 387-403
  17. V. Todorov
    Pages 404-416
  18. G. Willems, G. Pison, P. J. Rousseeuw, S. Van Aelst
    Pages 417-431

About these proceedings


Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.


Analysis Estimator Generalized linear model Linear discriminant analysis Measure Median Projection pursuit SAS Semiparametric Model Time series algorithms ants data analysis optimization programming

Editors and affiliations

  • Rudolf Dutter
    • 1
  • Peter Filzmoser
    • 1
  • Ursula Gather
    • 2
  • Peter J. Rousseeuw
    • 3
  1. 1.Institute of StatisticsVienna University of TechnologyViennaAustria
  2. 2.Statistics DepartmentUniversity of DortmundDortmundGermany
  3. 3.Department of Mathematics and Computer ScienceUniversity of AntwerpAntwerpBelgium

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2003
  • Publisher Name Physica, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-63241-9
  • Online ISBN 978-3-642-57338-5
  • Buy this book on publisher's site