Author(s): James R. Thompson
Praise for the First Edition "This…novel and highly stimulating book, which emphasizessolving real problems…should be widely read. It will have apositive and lasting effect on the teaching of modeling andstatistics in general." – Short Book Reviews This new edition features developments and real-worldexamples that showcase essential empirical modelingtechniques Successful empirical model building is founded on therelationship between data and approximate representations of thereal systems that generated that data. As a result, it is essentialfor researchers who construct these models to possess the specialskills 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 thebasic principles of empirical model building through a shrewdmixture of differential equations, computer-intensive methods, anddata. The book outlines both classical and new approaches andincorporates numerous real-world statistical problems thatillustrate modeling approaches that are applicable to a broad rangeof audiences, including applied statisticians and practicingengineers and scientists. The book continues to review models of growth and decay, systemswhere competition and interaction add to the complextiy of themodel while discussing both classical and non-classical dataanalysis methods. This Second Edition now features further coverageof momentum based investing practices and resampling techniques,showcasing their importance and expediency in the real world. Theauthor provides applications of empirical modeling, such ascomputer modeling of the AIDS epidemic to explain why North Americahas most of the AIDS cases in the First World and data-basedstrategies that allow individual investors to build their owninvestment portfolios. Throughout the book, computer-based analysisis emphasized and newly added and updated exercises allow readersto test their comprehension of the presented material. Empirical Model Building, Second Edition is a suitablebook for modeling courses at the upper-undergraduate andgraduate levels. It is also an excellent reference for appliedstatisticians and researchers who carry out quantitative modelingin their everyday work.