Robustness of Statistical Methods and Nonparametric Statistics (Theory and Decision Library B)

ISBN 10: 9027720762 / ISBN 13: 9789027720764

Published by Springer, 1986

About this Item

Unread, unmarked. No DJ. Gold/white boards, black letters. Thirty-nine papers. Tables, graphs.

Seller Inventory # 004715

Bibliographic Details

• Title: Robustness of Statistical Methods and Nonparametric Statistics (Theory and Decision Library B)
• Publisher: Springer
• Publication Date: 1986
• Language: English
• ISBN 10: 9027720762
• ISBN 13: 9789027720764
• Binding: Hardcover
• Condition: Fine

About this title

Synopsis

This volume contains most of the invited and contributed papers presented at the Conference on Robustness of Statistical Methods and Nonparametric Statistics held in the castle oj'Schwerin, Mai 29 - June 4 1983. This conference was organized by the Mathematical Society of the GDR in cooperation with the Society of Physical and Mathematical Biology of the GDR, the GDR-Region of the International Biometric Society and the Academy of Agricultural Sciences of the GDR. All papers included were thoroughly reviewed by scientist listed under the heading "Editorial Collabora­ tories·'. Some contributions, we are sorry to report, were not recommended for publi­ cation by the rf'vif'wers and do not appear in these proceedings. The editors thank the reviewers for their valuable comments and suggestions. The conference was organizf'd bv a Programme Committee, its chairman was Prof. Dr. Dieter Rasch (Research Centre of Animal Production, Dummerstorf-Rostock). The members of the Programme Committee were Prof. Dr. ,Johannes Adam (Martin-Luther-University Halle) Prof. Dr. Heinz Ahrens (Academy of Sciences of the GDR, Berlin) Doz. Dr. Jana Jureckova (Charles University Praha) Prof. Dr. Moti Lal Tiku (McMaster University, Hamilton, Ontario) The aim of the conference was to discuss several aspects of robustness but mainly to present new results regarding the robustness of classical statistical methods especially tests, confidence estimations, and selection procedures, and to compare their perfor­ mance with nonparametric procedures. Robustness in this sens~ is understood as intensivity against. violation of the normal assumption.