<p><strong>Statistical Modeling and Analysis for Complex Data Problems</strong><br/><em>Set:</em> Mathematics of Decision Making </p><p>Duchesne, Pierre; Rémillard, Bruno (Eds.) </p><p>2005, XIV, 330 p. 35 illus., Hardcover</p><p>ISBN: 978-0-387-24554-6</p><p> </p><p><br/><strong><em>About this book <br/></em></strong>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.</p><p><br/><strong><em>Written for:</em></strong><br/>Statisticians and applied mathematicians, plus researchers and librarians in OR, statistics, and computer science</p><p><br/><strong><em>Table of contents</em></strong><br/>-Foreword.<br/>- Contributing Authors.<br/>- Preface.<br/>- Dependence Properties of Meta-Elliptical Distributions.<br/>- The Statistical Significance of Palm Beach County.<br/>- Bayesian Functional Estimation of Hazard Rates for Randomly Right Censored Data Using Fourier Series Methods.<br/>- Conditions for the Validity of F-Ratio Tests for Treatment and Carryover Effects in Crossover Designs.<br/>- Bias in Estimating the Variance of K-Fold Cross Validation.<br/>- Effective Construction of Modified Histograms in Higher Dimensions.<br/>- On Robust Diagnostics at Individual Lags Using RA-ARX Estimators.<br/>- Bootstrap Confidence Intervals for Periodic Preventive Replacement Policies.<br/>- Statistics for Comparison of Two Independent cDNA Filter Microarrays.<br/>- Large Deviations for Interacting Processes in the Strong Topology.<br/>- Asymptotic Distribution of a Simple Linear Estimator for VARMA Models in Echolon Form.<br/>- Recent Results for Linear Time Series Models with Non Independent Innovations.<br/>- Filtering of Images for Detecting Multiple Targets Trajectories.<br/>- Optimzal Detection of Periodicities in Vector Autoregressive Models.<br/>- The Wilcoxon Signed-Rank Test for Cluster Correlated Data.</p><p> </p><p>
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