Pierre Duchesne / Bruno Rémillard (eds.)

Statistical Modeling and Analysis for Complex Data Problems

Herausgegeben:Duchesne, Pierre; Rémillard, Bruno

• Gebundenes Buch

Produktbeschreibung

Statistical Modeling and Analysis for Complex Data Problems treats some of today's more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors - largely from Montreal's GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes - present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.

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Produktdetails

• Mathematics of Decision Making
• Verlag: Springer / Springer US / Springer, Berlin
• Artikelnr. des Verlages: 978-0-387-24554-6
• 2005
• Seitenzahl: 344
• Erscheinungstermin: 12. April 2005
• Englisch
• Abmessung: 241mm x 160mm x 24mm
• Gewicht: 688g
• ISBN-13: 9780387245546
• ISBN-10: 0387245545
• Artikelnr.: 13921485

Autorenporträt

Pierre Duchesne, Universite de Montreal, QC, Canada / Bruno Rémillard, HEC Montreal, QC, Canada

Inhaltsangabe

Dependence Properties of Meta-Elliptical Distributions.- The Statistical Significance of Palm Beach County.- Bayesian Functional Estimation of Hazard Rates for Randomly Right Censored Data Using Fourier Series Methods.- Conditions for the Validity of F-Ratio Tests for Treatment and Carryover Effects in Crossover Designs.- Bias in Estimating the Variance of K-Fold Cross-Validation.- Effective Construction of Modified Histograms in Higher Dimensions.- On Robust Diagnostics at Individual Lags Using RA-ARX Estimators.- Bootstrap Confidence Intervals for Periodic Preventive Replacement Policies.- Statistics for Comparison of Two Independent cDNA Filter Microarrays.- Large Deviations for Interacting Processes in the Strong Topology.- Asymptotic Distribution of a Simple Linear Estimator for Varma Models in Echelon Form.- Recent Results for Linear Time Series Models with Non Independent Innovations.- Filtering of Images for Detecting Multiple Targets Trajectories.- Optimal Detection of Periodicities in Vector Autoregressive Models.- The Wilcoxon Signed-Rank Test for Cluster Correlated Data.