Empirical Model Building: Data, Models, and Reality (Wiley Series in Probability and Statistics)

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Praise for the First Edition"This...novel and highly stimulating book, which emphasizes solving real problems...should be widely read. It will have a positive and lasting effect on the teaching of modeling and statistics in general." - Short Book ReviewsThis new edition features developments and real-world examples that showcase essential empirical modeling techniquesSuccessful empirical model building is founded on the relationship between data and approximate representations of the real systems that generated that data. As a result, it is essential for researchers who construct these models to possess the special skills and techniques for producing results that are insightful, reliable, and useful. Empirical Model Building: Data, Models, and Reality, Second Edition presents a hands-on approach to the basic principles of empirical model building through a shrewd mixture of differential equations, computer-intensive methods, and data. The book outlines both classical and new approaches and incorporates numerous real-world statistical problems that illustrate modeling approaches that are applicable to a broad range of audiences, including applied statisticians and practicing engineers and scientists.The book continues to review models of growth and decay, systems where competition and interaction add to the complextiy of the model while discussing both classical and non-classical data analysis methods. This Second Edition now features further coverage of momentum based investing practices and resampling techniques, showcasing their importance and expediency in the real world. The author provides applications of empirical modeling, such as computer modeling of the AIDS epidemic to explain why North America has most of the AIDS cases in the First World and data-based strategies that allow individual investors to build their own investment portfolios. Throughout the book, computer-based analysis is emphasized and newly added and updated exercises allow readers to test their comprehension of the presented material.Empirical Model Building, Second Edition is a suitable book for modeling courses at the upper-undergraduate and graduate levels. It is also an excellent reference for applied statisticians and researchers who carry out quantitative modeling in their everyday work.

Author(s): James R. Thompson
Edition: 2
Publisher: Wiley
Year: 2011

Language: English
Pages: 459
Tags: Финансово-экономические дисциплины;Эконометрика;

CoverPage......Page 1
FrontMatter......Page 2
TitlePage......Page 4
CopyRight......Page 5
Dedication......Page 6
Contents......Page 8
Preface......Page 14
1 Models of Growth and Decay......Page 20
2 Models of Competition, Survival, and Combat......Page 58
3 Epidemics......Page 94
4 Bootstrapping......Page 130
5 Monte Carlo Solutions ofDifferential Equations......Page 150
6 SIMDAT, SIMEST, and Pseudoreality......Page 166
7 Exploratory Data Analysis......Page 194
8 Noise Killing Chaos......Page 212
9 A Primer in Bayesian Data Analysis......Page 228
10 Multivariate and Robust Procedures in Statistical Process Control......Page 248
11 Considerations for Optimization and Estimation in the Real (Noisy) World......Page 268
12 Utility and Group Preference......Page 292
13 A Primer in Sampling......Page 324
14 The Stock Market......Page 346
References......Page 404
Appendix A A Brief Introduction to Probability and Statistics......Page 406
Appendix B Statistical Tables......Page 444
Index......Page 446