Ebook: Statistical Modeling and Analysis for Complex Data Problems

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. Some of the areas and topics examined in the volume are: an analysis of complex survey data, the 2000 American presidential election in Florida, data mining, estimation of uncertainty for machine learning algorithms, interacting stochastic processes, dependent data & copulas, Bayesian analysis of hazard rates, re-sampling methods in a periodic replacement problem, statistical testing in genetics and for dependent data, statistical analysis of time series analysis, theoretical and applied stochastic processes, and an efficient non linear filtering algorithm for the position detection of multiple targets.

The book examines the methods and problems from a modeling perspective and surveys the state of current research on each topic and provides direction for further research exploration of the area.

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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. Some of the areas and topics examined in the volume are: an analysis of complex survey data, the 2000 American presidential election in Florida, data mining, estimation of uncertainty for machine learning algorithms, interacting stochastic processes, dependent data & copulas, Bayesian analysis of hazard rates, re-sampling methods in a periodic replacement problem, statistical testing in genetics and for dependent data, statistical analysis of time series analysis, theoretical and applied stochastic processes, and an efficient non linear filtering algorithm for the position detection of multiple targets.

The book examines the methods and problems from a modeling perspective and surveys the state of current research on each topic and provides direction for further research exploration of the area.

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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. Some of the areas and topics examined in the volume are: an analysis of complex survey data, the 2000 American presidential election in Florida, data mining, estimation of uncertainty for machine learning algorithms, interacting stochastic processes, dependent data & copulas, Bayesian analysis of hazard rates, re-sampling methods in a periodic replacement problem, statistical testing in genetics and for dependent data, statistical analysis of time series analysis, theoretical and applied stochastic processes, and an efficient non linear filtering algorithm for the position detection of multiple targets.

The book examines the methods and problems from a modeling perspective and surveys the state of current research on each topic and provides direction for further research exploration of the area.

Content:
Front Matter....Pages i-xiv
Dependence Properties of Meta-Elliptical Distributions....Pages 1-15
The Statistical Significance of Palm Beach County....Pages 17-40
Bayesian Functional Estimation of Hazard Rates for Randomly Right Censored Data Using Fourier Series Methods....Pages 41-57
Conditions for the Validity of F-Ratio Tests for Treatment and Carryover Effects in Crossover Designs....Pages 59-73
Bias in Estimating the Variance of K-Fold Cross-Validation....Pages 75-95
Effective Construction of Modified Histograms in Higher Dimensions....Pages 97-119
On Robust Diagnostics at Individual Lags Using RA-ARX Estimators....Pages 121-140
Bootstrap Confidence Intervals for Periodic Preventive Replacement Policies....Pages 141-159
Statistics for Comparison of Two Independent cDNA Filter Microarrays....Pages 161-178
Large Deviations for Interacting Processes in the Strong Topology....Pages 179-208
Asymptotic Distribution of a Simple Linear Estimator for Varma Models in Echelon Form....Pages 209-240
Recent Results for Linear Time Series Models with Non Independent Innovations....Pages 241-265
Filtering of Images for Detecting Multiple Targets Trajectories....Pages 267-280
Optimal Detection of Periodicities in Vector Autoregressive Models....Pages 281-307
The Wilcoxon Signed-Rank Test for Cluster Correlated Data....Pages 309-323

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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. Some of the areas and topics examined in the volume are: an analysis of complex survey data, the 2000 American presidential election in Florida, data mining, estimation of uncertainty for machine learning algorithms, interacting stochastic processes, dependent data & copulas, Bayesian analysis of hazard rates, re-sampling methods in a periodic replacement problem, statistical testing in genetics and for dependent data, statistical analysis of time series analysis, theoretical and applied stochastic processes, and an efficient non linear filtering algorithm for the position detection of multiple targets.

The book examines the methods and problems from a modeling perspective and surveys the state of current research on each topic and provides direction for further research exploration of the area.

Content:
Front Matter....Pages i-xiv
Dependence Properties of Meta-Elliptical Distributions....Pages 1-15
The Statistical Significance of Palm Beach County....Pages 17-40
Bayesian Functional Estimation of Hazard Rates for Randomly Right Censored Data Using Fourier Series Methods....Pages 41-57
Conditions for the Validity of F-Ratio Tests for Treatment and Carryover Effects in Crossover Designs....Pages 59-73
Bias in Estimating the Variance of K-Fold Cross-Validation....Pages 75-95
Effective Construction of Modified Histograms in Higher Dimensions....Pages 97-119
On Robust Diagnostics at Individual Lags Using RA-ARX Estimators....Pages 121-140
Bootstrap Confidence Intervals for Periodic Preventive Replacement Policies....Pages 141-159
Statistics for Comparison of Two Independent cDNA Filter Microarrays....Pages 161-178
Large Deviations for Interacting Processes in the Strong Topology....Pages 179-208
Asymptotic Distribution of a Simple Linear Estimator for Varma Models in Echelon Form....Pages 209-240
Recent Results for Linear Time Series Models with Non Independent Innovations....Pages 241-265
Filtering of Images for Detecting Multiple Targets Trajectories....Pages 267-280
Optimal Detection of Periodicities in Vector Autoregressive Models....Pages 281-307
The Wilcoxon Signed-Rank Test for Cluster Correlated Data....Pages 309-323
....