Robust Statistics, Data Analysis, and Computer Intensive Methods

Rieder Helmut

ISBN 10: 0387946608 / ISBN 13: 9780387946603

Editore: Springer, 1995

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Dati bibliografici

• Titolo: Robust Statistics, Data Analysis, and Computer Intensive Methods
• Editore: Springer
• Data di pubblicazione: 1995
• Lingua: Inglese
• ISBN 10: 0387946608
• ISBN 13: 9780387946603
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

The subsequent Workshop "Robust Statistics, Data Analysis and Computer Intensive Methods" in Schloss Thurnau, Friday until Sunday, June 9-12, was organized about the areas in statistics that Peter Huber himself has markedly shaped.

Contenuti

Bootstrap Variable-Selection and Confidence Sets.- Robust Estimation in the Logistic Regression Model.- The m out of n Bootstrap and Goodness of Fit Tests with Double Censored Data.- What Criterion for a Power Algorithm?.- Nonparametric Estimation of Global Functionals of Conditional Quantiles.- High Breakdown Point Estimators in Logistic Regression.- The Guinea Pig of Multiple Regression.- When is a p-Value a Good Measure of Evidence?.- Geometric Properties of Principal Curves in the Plane.- On Robust Estimation of Variograms in Geostatistics.- Advances in Nonparametric Function Estimation.- On the Philosophical Foundations of Statistics: Bridges to Huber’s work, and recent results.- Data Based Prototyping.- Robust Regression with a Categorical Covariable.- Robustness in Discriminant Analysis.- M-Estimation and Spatial Quantites.- Robust Statistical Methods in Interlab oratory Analytical Studies.- Estimating Distributions with a Fixed Number of Modes.- Implementing M -Estimators of the Gamma distribution.- Constrained M -Estimation for Regression.- Inference for the Direction of the Larger of Two Eigenvectors: The Case of Circular Elongation.- High Breakdown Point Designs.- On Bayesian Robustness: An Asymptotic Approach.- Computational Aspects of Trimmed Single-Link Clustering.- Interval Probability on Finite Sample Spaces.- On Consistency of Recursive Multivariate M-Estimators in Linear Models.- List of Participants.