Description
Book SynopsisPraise 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 Reviews
This new edition features developments and real-world examples that showcase essential empirical modeling techniques
Successful 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
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“It is also an excellent reference for applied statisticians and researchers who carry out quantitative modeling in their everyday work.” (Mathematical Reviews, 2012)
"Empirical Model Building, Second Edition is an excellent reference for applied statisticians and researchers who carry out quantitative modeling in their everyday work." (TMCnet.com, 18 January 2012)
Table of ContentsPreface.
1.Models of Growth and Decay.
2. Models of Competition, Survival, and Combat.
3. Epidemics.
4. Bootstrapping.
5. Monte-Carlo Solution of Differential Equations.
6. SIMEST, SMIDAT, and Psuedoreality.
7. Exploratory Data Analysis.
8. Noise Killing Chaos.
9. Bayesian Approaches.
10. Multivariate and Robust Procedures in Statistical Process Control.
11. Optimization and Estimation in the Real (Noisy) World.
12. Utility and Group Preference.
13. A Primer in Sampling.
14. Stock Market: Strategies Based on Data versus Strategies Based on Ideology.
Appendix A. A Brief Introduction to Probability and Statistics.
Appendix B. Statistical Tables.
