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Pierre Duchesne & Bruno Rémillard 
Statistical Modeling and Analysis for Complex Data Problems 

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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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Table of Content

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 c DNA 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.
Language English ● Format PDF ● Pages 324 ● ISBN 9780387245553 ● File size 16.0 MB ● Editor Pierre Duchesne & Bruno Rémillard ● Publisher Springer US ● City NY ● Country US ● Published 2005 ● Downloadable 24 months ● Currency EUR ● ID 2144087 ● Copy protection Social DRM

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