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Overview
Gives greater rigor to numerical treatments of stochastic models. Contains Monte Carlo and quasi-Monte Carlo techniques, simulation of major stochastic procedures, deterministic methods adapted to Markovian problems and special problems related to stochastic integral and differential equations. Simulation methods are given throughout the text as well as numerous exercises.
Synopsis
Gives greater rigor to numerical treatments of stochastic models. Contains Monte Carlo and quasi-Monte Carlo techniques, simulation of major stochastic procedures, deterministic methods adapted to Markovian problems and special problems related to stochastic integral and differential equations. Simulation methods are given throughout the text as well as numerous exercises.
Booknews
The authors offer this text for an introductory graduate course in an effort to add greater rigor to numerical treatment of stochastic processes, emphasizing simulation methods implemented with computer programs. They offer a broad introduction and theoretical background to the field, present the Monte Carlo, quasi-Monte Carlo, and shift methods, and explore problems raised by these methods. Features exercises and b&w graphs. Of interest to professional statisticians, engineers, and physical and social scientists, as well as students. Annotation c. Book News, Inc., Portland, OR (booknews.com)