Stochastic Processes

Stochastic Processes Review

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Stochastic Processes Feature

A nonmeasure theoretic introduction to stochastic processes. Considers its diverse range of applications and provides readers with probabilistic intuition and insight in thinking about problems. This revised edition contains additional material on compound Poisson random variables including an identity which can be used to efficiently compute moments; a new chapter on Poisson approximations; and coverage of the mean time spent in transient states as well as examples relating to the Gibb's sampler, the Metropolis algorithm and mean cover time in star graphs. Numerous exercises and problems have been added throughout the text.

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Stochastic Models in Operations Research, Vol. II: Stochastic Optimization

Stochastic Models in Operations Research, Vol. II: Stochastic Optimization Review

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Stochastic Models in Operations Research, Vol. II: Stochastic Optimization Feature

This 2nd volume of a 2-volume set explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. It introduces myopic optimal policies, Markov decision processes, generalizations of MDPs and related computational considerations, monotone optimal policies, and sequential games. 1984 edition. Includes 43 figures and 50 tables.

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Stochastic Models in Operations Research, Vol. I: Stochastic Processes and Operating Characteristics

Stochastic Models in Operations Research, Vol. I: Stochastic Processes and Operating Characteristics Review

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Stochastic Models in Operations Research, Vol. I: Stochastic Processes and Operating Characteristics Feature

This volume of a 2-volume set explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. Explores stochastic processes, operating characteristics of stochastic systems, and stochastic optimization. Comprehensive in its scope, this graduate-level text emphasizes the practical importance, intellectual stimulation, and mathematical elegance of stochastic models.

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