James Thompson – Simulation. A Modeler’s Approach

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James Thompson – Simulation. A Modeler’s Approach

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James Thompson – Simulation. A Modeler’s Approach

A distinctive, built-in remedy of laptop modeling and simulation “The future of science belongs to those willing to make the shift to simulation-based modeling,” predicts Rice Professor James Thompson, a number one modeler and computational statistician extensively identified for his authentic concepts and interesting fashion. He discusses strategies, accessible to anybody with a quick desktop laptop, for integrating simulation into the modeling course of with a purpose to create significant fashions of actual phenomena. Drawing from a wealth of expertise, he provides examples from buying and selling markets, oncology, epidemiology, statistical course of management, physics, public coverage, fight, real-world optimization, Bayesian analyses, and inhabitants dynamics. Dr. Thompson believes that, so removed from liberating us from the need of modeling, the quick laptop allows us to interact in life like fashions of processes in , for instance, economics, which haven’t been potential earlier as a result of easy stochastic fashions within the ahead temporal path usually turn into fairly unmanageably complicated when one is on the lookout for things like likelihoods. Thompson reveals how simulation could also be used to bypass the need of acquiring chance capabilities or moment-generating capabilities as a precursor to parameter estimation. Simulation: A Modeler’s Approach is a provocative and sensible information for professionals in utilized statistics in addition to engineers, scientists, laptop scientists, monetary analysts, and anybody with an curiosity within the synergy between information, fashions, and the digital laptop.

Table of Contents

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.

 

Author Information

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’s an elected member of the International Statistical Institute. In 1985, he obtained 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 utilized statistics. A frequent advisor to trade, he holds adjunct professorships on the M. D. Anderson Cancer Center and the University of Texas School of Public Health. He is the writer of ten books, together with Empirical Model Building, accessible from Wiley.

Reviews

With the appearance of sooner computer systems with comparatively massive storage amenities, simulation-based modeling is quickly being adopted in its place strategy to traditional top-down, assumptions-based, steady, stochastic and discrete differential equation modeling. Thompson presents an fascinating exposition to the artwork of simulation, and views “simulation approach” to modeling as a paradigm for life like evolutionary modeling. The guide is written in a really informal fashion, and background data in statistics is all that’s required to know the fabric contained therein. Thompson begins with an exposition of the technology of randomnumbers after which delves into quite a lot of particular matters, together with fashions for shares and derivatives, optimization and estimation in a loud world, Monte-Carlo options to differential equations, simulation evaluation of multivariate and sturdy procedures in statistical course of management, resampling-based exams, and a few exposition to modeling the AIDS epidemic. Several helpful algorithms, drawback units, and references to straightforward simulation packages are offered. Short chapter bibliographies; wide selection of examples. The guide may very well be used as a useful resource for starting graduate college students and professionals in utilized statistics, laptop science, economics and finance, engineering, and the pure sciences. Highly really useful. Graduate college students; school; professionals. (CHOICE, April 2001, Vol. 38, No. 8)

“…an eclectic survey of computing methods…lively and interesting…the wide variety of example certainly helps bring the material to life.” (Journal of the American Statistical Association, Vol. 97, No. 457, March 2002)

“…a very useful and entertaining book…a great reference book…contains some valuable material and philosophy that is unavailable anywhere else.” (IIE Transactions)

“…often entertaining…the level of detain and relevance is appropriate…a worthwhile read for model builders comfortable with both mathematics and simulation.” (Complexity, Vol. 7, No. 2, 2002)

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