Dieses Buch will zeigen, wie sich Simulationen bei der Entwicklung geeigneter Modelle für reale Vorgänge nutzbringend anwenden lassen. Wichtigstes Ziel dabei ist es, die Simulation als Bindeglied zwischen Näherungswerten und Modellen einzusetzen, Hypothesen zu testen und ein Gefühl für die Variabilität der Daten zu bekommen. Zahlreiche Fallstudien fördern das konzeptuelle Denken. (01/00)

JAMES R. THOMPSON, PhD, is Professor of Statistics at Rice University. A Fellow of the American Statistical Association and the Institute of Mathematical Statistics, he is an elected member of the International Statistical Institute. In 1985, he received the ASA's Don Owen Award, and in 1991, he was awarded the U.S. Army's Samuel S. Wilks Medal for his work in applied statistics. A frequent consultant to industry, he holds adjunct professorships at the M. D. Anderson Cancer Center and the University of Texas School of Public Health. He is the author of ten books, including Empirical Model Building, available from Wiley.

The Generation of "Random" Numbers.
Random Quadrature.
Monte Carlo Solutions of Differential Equations.
Markov Chains, Poisson Processes and Linear Equations.
SIMEST, SIMDAT, and Pseudoreality.
Models for Stocks and Derivatives.
Simulation Assessment of Multivariate and Robust Procedures in Statistical Process Control.
Noise and Chaos.
Bayesian Approaches.
Resampling Based Tests.
Optimization and Estimation in a Noisy World.
Modeling the USA AIDS Epidemic: Exploration, Simulation and Conjecture.
Appendices.
Index.