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基本説明
Introduces students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences. New chapter on Brownian motion and related processes.
Full Description
Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, Introduction to Stochastic Modeling, Fourth Edition, bridges the gap between basic probability and an intermediate level course in stochastic processes. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of simple stochastic analysis to realistic problems.
New to this edition:
Realistic applications from a variety of disciplines integrated throughout the text, including more biological applications
Plentiful, completely updated problems
Completely updated and reorganized end-of-chapter exercise sets, 250 exercises with answers
New chapters of stochastic differential equations and Brownian motion and related processes
Additional sections on Martingale and Poisson process
Contents
IntroductionConditional Probability and Conditional ExpectationMarkov Chains: IntroductionThe Long Run Behavior of Markov ChainsPoisson ProcessesContinuous Time Markov ChainsRenewal PhenomenaBrownian Motion and Related ProcessesQueueing Systems Random EvolutionsCharacteristic Functions and Their Applications
