Statistical Modeling and Analysis for Complex Data Problems

by Pierre Duchesne (Editor), Bruno Rémillard (Editor)

Overview

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 shastic processes – present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.

Product Details

ISBN-13:	9781441937513
Publisher:	Springer US
Publication date:	10/29/2010
Edition description:	Softcover reprint of hardcover 1st ed. 2005
Pages:	324
Product dimensions:	6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

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.