001484132 000__ 04572cam\\22005417i\4500
001484132 001__ 1484132
001484132 003__ OCoLC
001484132 005__ 20240117003314.0
001484132 006__ m\\\\\o\\d\\\\\\\\
001484132 007__ cr\cn\nnnunnun
001484132 008__ 231117s2023\\\\si\a\\\\o\\\\\000\0\eng\d
001484132 019__ $$a1407835590$$a1409030037
001484132 020__ $$a9789819956012$$q(electronic bk.)
001484132 020__ $$a9819956013$$q(electronic bk.)
001484132 020__ $$z9819956005
001484132 020__ $$z9789819956005
001484132 0247_ $$a10.1007/978-981-99-5601-2$$2doi
001484132 035__ $$aSP(OCoLC)1409590395
001484132 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dYDX$$dOCLCQ$$dOCLCO$$dYDX$$dOCLCO
001484132 049__ $$aISEA
001484132 050_4 $$aQA274$$b.M334 2023
001484132 08204 $$a519.2302855133$$223/eng/20231117
001484132 1001_ $$aMadhira, Sivaprasad,$$eauthor.
001484132 24510 $$aIntroduction to stochastic processes using R /$$cSivaprasad Madhira, Shailaja Deshmukh.
001484132 264_1 $$aSingapore :$$bSpringer,$$c2023.
001484132 300__ $$a1 online resource (651 pages) :$$billustrations (black and white, and color).
001484132 336__ $$atext$$btxt$$2rdacontent
001484132 337__ $$acomputer$$bc$$2rdamedia
001484132 338__ $$aonline resource$$bcr$$2rdacarrier
001484132 5050_ $$aBasics of Stochastic Processes -- Markov Chains -- Long-run Behaviour of Markov Chains -- Random Walks -- Bienayme Galton Watson Branching Process -- Continuous Time Markov Chains -- Poisson Process -- Birth and Death Processes -- Brownian Motion Process -- Renewal Process -- Solutions Conceptual Exercises.
001484132 506__ $$aAccess limited to authorized users.
001484132 520__ $$aThis textbook presents some basic stochastic processes, mainly Markov processes. It begins with a brief introduction to the framework of stochastic processes followed by the thorough discussion on Markov chains, which is the simplest and the most important class of stochastic processes. The book then elaborates the theory of Markov chains in detail including classification of states, the first passage distribution, the concept of periodicity and the limiting behaviour of a Markov chain in terms of associated stationary and long run distributions. The book first illustrates the theory for some typical Markov chains, such as random walk, gambler's ruin problem, Ehrenfest model and Bienayme-Galton-Watson branching process; and then extends the discussion when time parameter is continuous. It presents some important examples of a continuous time Markov chain, which include Poisson process, birth process, death process, birth and death processes and their variations. These processes play a fundamental role in the theory and applications in queuing and inventory models, population growth, epidemiology and engineering systems. The book studies in detail the Poisson process, which is the most frequently applied stochastic process in a variety of fields, with its extension to a renewal process. The book also presents important basic concepts on Brownian motion process, a stochastic process of historic importance. It covers its few extensions and variations, such as Brownian bridge, geometric Brownian motion process, which have applications in finance, stock markets, inventory etc. The book is designed primarily to serve as a textbook for a one semester introductory course in stochastic processes, in a post-graduate program, such as Statistics, Mathematics, Data Science and Finance. It can also be used for relevant courses in other disciplines. Additionally, it provides sufficient background material for studying inference in stochastic processes. The book thus fulfils the need of a concise but clear and student-friendly introduction to various types of stochastic processes.
001484132 588__ $$aDescription based on print version record.
001484132 650_6 $$aProcessus stochastiques$$xInformatique.
001484132 650_6 $$aR (Langage de programmation)
001484132 650_0 $$aStochastic processes$$xData processing.
001484132 650_0 $$aR (Computer program language)$$0(DLC)sh2002004407
001484132 655_0 $$aElectronic books.
001484132 7001_ $$aDeshmukh, Shailaja,$$eauthor.
001484132 77608 $$iPrint version:$$aMADHIRA, SIVAPRASAD. DESHMUKH, SHAILAJA.$$tINTRODUCTION TO STOCHASTIC PROCESSES USING R.$$d[Place of publication not identified] : SPRINGER VERLAG, SINGAPOR, 2023$$z9819956005$$w(OCoLC)1390118765
001484132 852__ $$bebk
001484132 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-5601-2$$zOnline Access$$91397441.1
001484132 909CO $$ooai:library.usi.edu:1484132$$pGLOBAL_SET
001484132 980__ $$aBIB
001484132 980__ $$aEBOOK
001484132 982__ $$aEbook
001484132 983__ $$aOnline
001484132 994__ $$a92$$bISE