03765nam 22006135 450 991030015740332120200630072242.03-642-40523-110.1007/978-3-642-40523-5(CKB)3710000000078652(MH)013863957-4(SSID)ssj0001049494(PQKBManifestationID)11602091(PQKBTitleCode)TC0001049494(PQKBWorkID)11020042(PQKB)10276716(DE-He213)978-3-642-40523-5(MiAaPQ)EBC3107081(PPN)17611484X(EXLCZ)99371000000007865220131028d2014 u| 0engurnn|008mamaatxtrdacontentnrdamediancrdacarrierAn Introduction to Markov Processes /by Daniel W. Stroock2nd ed. 2014.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2014.1 online resource (xv, 203 pages )Graduate Texts in Mathematics,0072-5285 ;230Bibliographic Level Mode of Issuance: Monograph3-642-40522-3 Includes bibliographical references (page 199) and index.Preface -- Random Walks, a Good Place to Begin -- Doeblin's Theory for Markov Chains -- Stationary Probabilities -- More about the Ergodic Theory of Markov Chains -- Markov Processes in Continuous Time -- Reversible Markov Processes -- A minimal Introduction to Measure Theory -- Notation -- References -- Index.This book provides a rigorous but elementary introduction to the theory of Markov Processes on a countable state space. It should be accessible to students with a solid undergraduate background in mathematics, including students from engineering, economics, physics, and biology. Topics covered are: Doeblin's theory, general ergodic properties, and continuous time processes. Applications are dispersed throughout the book. In addition, a whole chapter is devoted to reversible processes and the use of their associated Dirichlet forms to estimate the rate of convergence to equilibrium. These results are then applied to the analysis of the Metropolis (a.k.a simulated annealing) algorithm. The corrected and enlarged 2nd edition contains a new chapter in which the author develops computational methods for Markov chains on a finite state space. Most intriguing is the section with a new technique for computing stationary measures, which is applied to derivations of Wilson's algorithm and Kirchoff's formula for spanning trees in a connected graph.Graduate Texts in Mathematics,0072-5285 ;230ProbabilitiesDynamicsErgodic theoryProbability Theory and Stochastic Processeshttps://scigraph.springernature.com/ontologies/product-market-codes/M27004Dynamical Systems and Ergodic Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/M1204XProbabilities.Dynamics.Ergodic theory.Probability Theory and Stochastic Processes.Dynamical Systems and Ergodic Theory.519.2Stroock Daniel Wauthttp://id.loc.gov/vocabulary/relators/aut42628BOOK9910300157403321Introduction to Markov processes33145UNINAThis Record contains information from the Harvard Library Bibliographic Dataset, which is provided by the Harvard Library under its Bibliographic Dataset Use Terms and includes data made available by, among others the Library of Congress