Markov Chains (Cambridge Series in Statistical and Probabilistic Mathematics, S,

Description: About this productProduct IdentifiersPublisherCambridge University PressISBN-100521633966ISBN-139780521633963eBay Product ID (ePID)976635Product Key FeaturesNumber of Pages254 PagesPublication NameMarkov ChainsLanguageEnglishPublication Year1998SubjectProbability & Statistics / Stochastic Processes, Probability & Statistics / GeneralTypeTextbookSubject AreaMathematicsAuthorJ. R. NorrisSeriesCambridge Series in Statistical and Probabilistic Mathematics Ser.FormatTrade PaperbackDimensionsItem Height0.7 inItem Weight16.7 OzItem Length10 inItem Width7 inAdditional Product FeaturesIntended AudienceScholarly & ProfessionalLCCN96-031570Reviews'My overall impression of this book is very positive â€¦ this is the best introduction to the subject that I have come across.' Contemporary Physics, ‘This is an admirable book, treating the topic with mathematical rigour and clarity, mixed with helpful informality; and emphasising numerous applications to a wide range of subjects.’D. V. Lindley, The Mathematical Gazette, 'We recently based a seminar on this book â€¦ it is well suited for an elementary, technically modest, but still rigorous introduction into the heart of a lively and relevant area of stochastic processes.' M. Scheutzow, Zentralblatt MATH, 'My overall impression of this book is very positive ... this is the best introduction to the subject that I have come across.' Contemporary Physics, ‘An instructor looking for a suitable text, at the level of a Master of Mathematics degree, can use this book with confidence and enthusiasm.’John Haigh, University of Sussex, ‘We recently based a seminar on this book … it is well suited for an elementary, technically modest, but still rigorous introduction into the heart of a lively and relevant area of stochastic processes.’M. Scheutzow, Zentralblatt MATH, ‘My overall impression of this book is very positive … this is the best introduction to the subject that I have come across.’Contemporary Physics, "...impressive ....I heartily recommend this book....this is the best book available summarizing the theory of Markov Chains....Norris achieves for Markov Chains what Kingman has so elegantly achieved for Poisson processes....Such creative tinkering will be a pleasure to many teachers." Bulletin of Mathematical Biology, 'An instructor looking for a suitable text, at the level of a Master of Mathematics degree, can use this book with confidence and enthusiasm.' John Haigh, University of Sussex, 'This is an admirable book, treating the topic with mathematical rigour and clarity, mixed with helpful informality; and emphasising numerous applications to a wide range of subjects.' D. V. Lindley, The Mathematical Gazette, 'We recently based a seminar on this book ... it is well suited for an elementary, technically modest, but still rigorous introduction into the heart of a lively and relevant area of stochastic processes.' M. Scheutzow, Zentralblatt MATHSeries Volume NumberSeries Number 2CLASSIFICATION_METADATA{"IsNonfiction":["No"],"IsOther":["No"],"IsAdult":["No"],"MuzeFormatDesc":["Trade Paperback"],"IsChildren":["No"],"Genre":["MATHEMATICS"],"Topic":["Probability & Statistics / General","Probability & Statistics / Stochastic Processes"],"IsTextBook":["Yes"],"IsFiction":["No"]}IllustratedYesTable Of ContentIntroduction; 1. Discrete-time Markov chains; 2. Continuous-time Markov chains I; 3. Continuous-time Markov chains II; 4. Further theory; 5. Applications; Appendix; Probability and measure; Index.SynopsisA textbook for students with some background in probability that develops quickly a rigorous theory of Markov chains and shows how actually to apply it, e.g. to simulation, economics, optimal control, genetics, queues and many other topics, and exercises and examples drawn both from theory and practice., In this rigorous account the author studies both discrete-time and continuous-time chains. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials, in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and a careful selection of exercises and examples drawn both from theory and practice. This is an ideal text for seminars on random processes or for those that are more oriented towards applications, for advanced undergraduates or graduate students with some background in basic probability theory., Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov chains and quickly develops a coherent and rigorous theory whilst showing also how actually to apply it. Both discrete-time and continuous-time chains are studied. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and exercises and examples drawn both from theory and practice. It will therefore be an ideal text either for elementary courses on random processes or those that are more oriented towards applications.LC Classification NumberQA274.7 .N67 1998Copyright Date1998ebay_catalog_id4

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