Robustness of statistical methods and nonparametric statistics

書誌事項

Robustness of statistical methods and nonparametric statistics

edited by Dieter Rasch and Moti Lal Tiku

(Theory and decision library, ser. B . Mathematical and statistical methods)

D. Reidel, c1984

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タイトル別名

Robustness of statistical methods

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注記

A selection of papers presented at a conference organized by the Mathematical Society of the GDR, held in Schwerin on May 29 - June 4 1983

Includes bibliographical references

内容説明・目次

内容説明

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.

目次

Behaviour of L-estimators of location from the point of view of large deviations.- Simulation in research on linear models.- Note about solutions of asymptotic minimax test problems for special capacities.- Some remarks on the comparison of means in the case of correlated errors.- Robustness of multiple comparisons against variance heterogeneity.- The power of run test verifying the hypothesis of model linearity.- The robustness of selection procedures investigated by a combinational method.- Results of comparisons between different random number generators.- Robustness of the two-sample sequential t-test.- Optimal designs for contaminated linear regression.- Systems of one-dimensional continuous distributions and their application in simulation studies.- A combinatorial method in robustness research and two applications.- Analogy of the linear regression and the two-sample problem in robustness investigations.- Rates of consistency of classical one-sided tests.- Asymptotic robustness of Bayesian decision rules in statistical decision theory.- Ranks, standardized ranks and standardized aligned ranks in the analysis of Friedman's block design.- Chernoff type bounds of errors in hypothesis testing of diffusion processes.- Power simulation with the same random sequences under the null hypothesis and the alternative.- Robustness of two-sample tests for variances.- The influence of different shapes of distributions with the same first four moments on robustness.- Robust Bayes regression estimation under weak prior knowledge.- Distribution of the maximal GAP in a sample and its application for outlier detection.- Robustness of the two-sample t-test.- Robustness of three sequential one-sample tests against non-normality.- A test for exponential regression and its robustness.- Comparison of break points of estimators.- The robustness of some statistical tests. The Multivariate case.- Tests for independence in the family of continuous bivariate distributions with finite contingency.- Robustness of many-one statistics.- Testing hypotheses in nonlinear regression for nonnormal distributions.- The bootstrap in nonlinear regression.- Sharp inequalities for error probabilities of tests under moment conditions.- Simulation studies on robustness of the t- and u-test against truncation of the normal distribution.- Robust location-tests and classification procedures.- Minimax-linear estimation under incorrect prior information.- The roubstness of some procedures for the two-sample location problem - a simulation study (concept).- On the measurement of the tests robustness.- A Robust Estimate of Variance in a Linear Model.- Minimax-versus robust experimental designs: Two simple examples.

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