Robustness of Statistical Methods and Nonparametric Statistics

Inhaltsverzeichnis

• 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 itsrobustness.
• 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.