Statistical Modeling and Analysis for Complex Data Problems

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Pierre Duchesne, Bruno Rémillard
Springer Science & Business Media, Dec 5, 2005 - Mathematics - 324 pages
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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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Contents

The Statistical Significance of Palm Beach County
17
Bayesian Functional Estimation of Hazard Rates for Randomly
41
Conditions for the Validity of F Ratio Tests for Treatment and 59
58
Bias in Estimating the Variance of K Fold CrossValidation
75
Effective Construction of Modified Histograms in Higher Dimensions 97
103
On Robust Diagnostics at Individual Lags Using RAARX Estimators
121
Bootstrap Confidence Intervals for Periodic Preventive Replace
141
Statistics for Comparison of Two Independent cDNA Filter Microarrays 161
160
Recent Results for Linear Time Series Models with Non Indepen
241
13
254
Filtering of Images for Detecting Multiple Targets Trajectories
267
14
273
Optimal Detection of Periodicities in Vector Autoregressive Models
281
15
297
The Wilcoxon SignedRank Test for Cluster Correlated Data 309
308
Copyright

Asymptotic Distribution of a Simple Linear Estimator for VARMA
209

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