Book Description This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models, and techniques, along with appropriate applications. Volume 1 begins with an introductory chapter by Gilbert Saporta, a leading expert in the field, who summarizes the developments in data analysis over the last 50 years. The book is then divided into three parts: Part 1 presents clustering and regression cases; Part 2 examines grouping and decomposition, GARCH and threshold models, structural equations, and SME modeling; and Part 3 presents symbolic data analysis, time series and multiple choice models, modeling in demography, and data mining. Show and hide more
Table of Contents
Cover Preface Introduction: 50 Years of Data Analysis: From Exploratory Data Analysis to Predictive Modeling and Machine Learning I.1. The revolt against mathematical statistics I.2. EDA and unsupervised methods for dimension reduction I.3. Predictive modeling I.4. Conclusion I.5. References PART 1: Clustering and Regression 1 Cluster Validation by Measurement of Clustering Characteristics Relevant to the User 1.1. Introduction 1.2. General notation 1.3. Aspects of cluster validity 1.4. Aggregation of indexes 1.5. Random clusterings for calibrating indexes 1.6. Examples 1.7. Conclusion 1.8. Acknowledgment 1.9. References 2 Histogram-Based Clustering of Sensor Network Data 2.1. Introduction 2.2. Time series data stream clustering 2.3. Results on real data 2.4. Conclusions 2.5. References 3 The Flexible Beta Regression Model 3.1. Introduction 3.2. The FB distribution 3.3. The FB regression model 3.4. Bayesian inference 3.5. Illustrative application 3.6. Conclusion 3.7. References 4 S-weighted Instrumental Variables 4.1. Summarizing the previous relevant results 4.2. The notations, framework, conditions and main tool 4.3. S-weighted estimator and its consistency 4.4. S-weighted instrumental variables and their consistency 4.5. Patterns of results of simulations 4.6. Acknowledgment 4.7. References PART 2: Models and Modeling 5 Grouping Property and Decomposition of Explained Variance in Linear Regression 5.1. Introduction 5.2. CAR scores 5.3. Variance decomposition methods and SVD 5.4. Grouping property of variance decomposition methods 5.5. Conclusions 5.6. References 6 On GARCH Models with Temporary Structural Changes 6.1. Introduction 6.2. The model 6.3. Identification 6.4. Simulation 6.5. Application 6.6. Concluding remarks 6.7. References 7 A Note on the Linear Approximation of TAR Models 7.1. Introduction 7.2. Linear representations and linear approximations of nonlinear models 7.3. Linear approximation of the TAR model 7.4. References 8 An Approximation of Social Well-Being Evaluation Using Structural Equation Modeling 8.1. Introduction 8.2. Wellness 8.3. Social welfare 8.4. Methodology 8.5. Results 8.6. Discussion 8.7. Conclusions 8.8. References 9 An SEM Approach to Modeling Housing Values 9.1. Introduction 9.2. Data 9.3. Analysis 9.4. Conclusions 9.5. References 10 Evaluation of Stopping Criteria for Ranks in Solving Linear Systems 10.1. Introduction 10.2. Methods 10.3. Formulation of linear systems 10.4. Stopping criteria 10.5. Numerical experimentation of stopping criteria 10.6. Conclusions 10.7. Acknowledgments 10.8. References 11 Estimation of a Two-Variable Second-Degree Polynomial via Sampling 11.1. Introduction 11.2. Proposed method 11.3. Experimental approaches 11.4. Conclusions 11.5. References PART 3: Estimators, Forecasting and Data Mining 12 Displaying Empirical Distributions of Conditional Quantile Estimates: An Application of Symbolic Data Analysis to the Cost Allocation Problem in Agriculture 12.1. Conceptual framework and methodological aspects of cost allocation 12.2. The empirical model of specific production cost estimates 12.3. The conditional quantile estimation 12.4. Symbolic analyses of the empirical distributions of specific costs 12.5. The visualization and the analysis of econometric results 12.6. Conclusion 12.7. Acknowledgments 12.8. References 13 Frost Prediction in Apple Orchards Based upon Time Series Models 13.1. Introduction 13.2. Weather database 13.3. ARIMA forecast model 13.4. Model building 13.5. Evaluation 13.6. ARIMA model selection 13.7. Conclusions 13.8. Acknowledgments 13.9. References 14 Efficiency Evaluation of Multiple-Choice Questions and Exams 14.1. Introduction 14.2. Exam efficiency evaluation 14.3. Real-life experiments and results 14.4. Conclusions 14.5. References 15 Methods of Modeling and Estimation in Mortality 15.1. Introduction 15.2. The appearance of life tables 15.3. On the law of mortality 15.4. Mortality and health 15.5. An advanced health state function form 15.6. Epilogue 15.7. References 16 An Application of Data Mining Methods to the Analysis of Bank Customer Profitability and Buying Behavior 16.1. Introduction 16.2. Data set 16.3. Short-term forecasting of customer profitability 16.4. Churn prediction 16.5. Next-product-to-buy 16.6. Conclusions and future research 16.7. References List of Authors Index End User License Agreement