05526nam 2200733Ia 450 991101964140332120200520144314.097866102718329780470864289047086428197812802718301280271833978047035833704703583359780470013632047001363X(CKB)1000000000019117(StDuBDS)AH13353597(SSID)ssj0000296464(PQKBManifestationID)11253823(PQKBTitleCode)TC0000296464(PQKBWorkID)10321749(PQKB)10665671(SSID)ssj0000155476(PQKBManifestationID)12054104(PQKBTitleCode)TC0000155476(PQKBWorkID)10112233(PQKB)10819822(MiAaPQ)EBC158138(PPN)137734271(Perlego)2748696(EXLCZ)99100000000001911720021118d2003 uy 0engur|||||||||||txtccrA first course in stochastic models /Henk C. Tijms2nd ed.Chichester, England ;Hoboken, NJ Wileyc20031 online resource (450 p.) Bibliographic Level Mode of Issuance: Monograph9780471498810 0471498815 9780471498803 0471498807 Includes bibliographical references and index.Preface. The Poisson Process and Related Processes. Renewal-Reward Processes. Discrete-Time Markov Chains. Continuous-Time Markov Chains. Markov Chains and Queues. Discrete-Time Markov Decision Processes. Semi-Markov Decision Processes. Advanced Renewal Theory. Algorithmic Analysis of Queueing Models. Appendices. Appendix A: Useful Tools in Applied Probability. Appendix B: Useful Probability Distributions. Appendix C: Generating Functions. Appendix D: The Discrete Fast Fourier Transform. Appendix E: Laplace Transform Theory. Appendix F: Numerical Laplace Inversion. Appendix G: The Root-Finding Problem. References. Index.An integrated presentation of theory, applications and algorithms that demonstrates how useful simple stochastic models can be for gaining insight into the behaviour of complex stochastic systems.The field of applied probability has changed profoundly in the past twenty years. The development of computational methods has greatly contributed to a better understanding of the theory. A First Course in Stochastic Models provides a self-contained introduction to the theory and applications of stochastic models. Emphasis is placed on establishing the theoretical foundations of the subject, thereby providing a framework in which the applications can be understood. Without this solid basis in theory no applications can be solved. Provides an introduction to the use of stochastic models through an integrated presentation of theory, algorithms and applications. Incorporates recent developments in computational probability. Includes a wide range of examples that illustrate the models and make the methods of solution clear. Features an abundance of motivating exercises that help the student learn how to apply the theory. Accessible to anyone with a basic knowledge of probability. A First Course in Stochastic Models is suitable for senior undergraduate and graduate students from computer science, engineering, statistics, operations resear ch, and any other discipline where stochastic modelling takes place. It stands out amongst other textbooks on the subject because of its integrated presentation of theory, algorithms and applications. The field of applied probability has changed profoundly in the past twenty years. The development of computational methods has greatly contributed to a better understanding of the theory. A First Course in Stochastic Models provides a self-contained introduction to the theory and applications of stochastic models. Emphasis is placed on establishing the theoretical foundations of the subject, thereby providing a framework in which the applications can be understood. Without this solid basis in theory no applications can be solved. Provides an introduction to the use of stochastic models through an integrated presentation of theory, algorithms and applications. Incorporates recent developments in computational probability. Includes a wide range of examples that illustrate the models and make the methods of solution clear. Features an abundance of motivating exercises that help the student learn how to apply the theory. Accessible to anyone with a basic knowledge of probability. A First Course in Stochastic Models is suitable for senior undergraduate and graduate students from computer science, engineering, statistics, operations resear ch, and any other discipline where stochastic modelling takes place. It stands out amongst other textbooks on the subject because of its integrated presentation of theory, algorithms and applications.Stochastic processesProbabilitiesStochastic processes.Probabilities.519.2/3Tijms H. C56125MiAaPQMiAaPQMiAaPQBOOK9911019641403321First course in stochastic models736670UNINA