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MODA4 — Advances in Model-Oriented Data Analysis: Proceedings of the 4th International Workshop in Spetses, Greece June 5–9, 1995: Contributions to Statistics

Editat de Christos P. Kitsos, Werner G. Müller
en Limba Engleză Paperback – 17 mai 1995
This volume is the proceedings of the 4th International Workshop on Model-Oriented Data Analysis. This series of events originated in 1987 at a meeting in Eisenach, that successfully brought together scientists from numerous countries of the 'East ' and 'West'. Now that this distinction is obsolete dialogue has been greatly facilitated, providing opportunities for this dialogue, however, is as vital as ever. The present meeting at Spetses, Greece from 5th to 9th of June 1995 again assembles statisticians from all over the world as this book documents. The hospitality offered by the University of Economics of Athens and the Korgialenios School made it possible to organize this workshop. The editors are also grateful to Intracom (Greece), the Ionian Bank and the Procter & Gamble Company (USA) for their generous support. We would particularly like to mention Dr. Michael Meredith, who being our contact person at Procter & Gamble, enabled us to publish these proceedings. Further thanks go to Dr. Peter Schuster from Physica Verlag Heidelberg for his continuing support of the project. The contributions to this volume were carefully selected from the submissions by the editors after a one stage refereeing process. We would like to thank the members of the MODA committee, A.C. Atkinson, R.D. Cook, V.V. Fedorov, P.Hackl, H. Lauter, B.Torsney, LN. Vuchkov, H.P.Wynn,and A.A. Zhigljavsky, who not only defined the main topics of the workshop, but also served as the referees.
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Specificații

ISBN-13: 9783790808643
ISBN-10: 3790808644
Pagini: 312
Ilustrații: XIV, 297 p.
Dimensiuni: 210 x 297 x 16 mm
Greutate: 0.75 kg
Editura: Physica-Verlag HD
Colecția Physica
Seria Contributions to Statistics

Locul publicării:Heidelberg, Germany

Public țintă

Research

Cuprins

I Optimal Design.- Optimal Designs for Time—Dependent Responses.- Robust Optimal Designs with Constraints.- Bayesian Designs for Approximate Normality.- Simulation Approach to One-Stage and Sequential Optimal Design Problems.- One Bound for the Mean Duration of Sequential Testing Homogeneity.- MV-optimization in Simple Linear Regression.- On the Support Points of D-Optimal Nonlinear Experimental Designs for Chemical Kinetics.- Designing Experiments for Additive Nonlinear Models.- D-Optimal Designs for Generalized Linear Models.- Further Results on Optimal Designs for Generalized Tic Polynomials on the Simplex.- Relations between Spring and Chemical Balance Weighing Designs with the Diagonal Covariance Matrix of Errors.- Optimal Design for Experiments with Potentially Failing Trials.- Regression Design for One-Dimensional Subspaces.- D-Optimal First Order Saturated Designs with n ? 2mod4 Observations.- On Information Matrices for Fixed and Random Parameters in Generally Balanced Experimental Block Designs.- Estimation of Parameters in Factorial Triallel Analysis for BIB Design — the Mixed Model.- On the Optimality of Certain Nested Block Designs under a Mixed Effects Model.- Construction of A-Optimum Cross-Over Designs.- An Algorithm for Sampling Optimization for Semivariogram Estimation.- II Estimation and Optimization.- Multivariate Transformations, Regression Diagnostics and Seemingly Unrelated Regression.- Regression Rank Scores: Asymptotic Linearity and RR-Estimators.- The Asymptotic Distribution of Regression Parameters.- Some Simulation Results on Cross-Validation and Competitors for Model Choice.- Robust Estimation of Non-linear Aspects.- Robust Minimax Adaptive M-Estimators of Regression Parameters.- Modeling Heterogeneity and Extraneous Variation UsingWeighted Distributions.- Gibbs Sampling for ARCH Models in Finance.- A Class of Recursive Algorithms Using Non-parametric Methods with Constant Step Size and Window Width: A Numerical Study.- Robust Design of Products Depending on Both Qualitative and Quantitative Factors.- Improving on Golden-Section Optimisation for Locally Symmetric Functions.