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＜電子ブック＞
Basics of Applied Stochastic Processes / by Richard Serfozo
(Probability and Its Applications)

版	1st ed. 2009.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	2009
本文言語	英語
大きさ	XIV, 443 p : online resource
著者標目	*Serfozo, Richard author SpringerLink (Online service)
件　名	LCSH:Probabilities LCSH:Mathematical models FREE:Probability Theory FREE:Mathematical Modeling and Industrial Mathematics
一般注記	Markov Chains -- Renewal and Regenerative Processes -- Poisson Processes -- Continuous-Time Markov Chains -- Brownian Motion Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Markov chains in discrete and continuous time, renewal and regenerative processes, Poisson processes, and Brownian motion. This volume gives an in-depth description of the structure and basic properties of these stochastic processes. A main focus is on equilibrium distributions, strong laws of large numbers, and ordinary and functional central limit theorems for cost and performance parameters. Although these results differ for various processes, they have a common trait of being limit theorems for processes with regenerative increments. Extensive examples and exercises show how to formulate stochastic models of systems as functions of a system’s data and dynamics, and how to represent and analyze cost and performance measures. Topics include stochastic networks, spatial and space-time Poisson processes, queueing, reversible processes, simulation, Brownian approximations, and varied Markovian models. The technical level of the volume is between that of introductory texts that focus on highlights of applied stochastic processes, and advanced texts that focus on theoretical aspects of processes. Intended readers are researchers and graduate students in mathematics, statistics, operations research, computer science, engineering, and business HTTP:URL=https://doi.org/10.1007/978-3-540-89332-5

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