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The Resource An Introduction to Markov Processes, by Daniel W. Stroock, (electronic resource)
An Introduction to Markov Processes, by Daniel W. Stroock, (electronic resource)
Resource Information
The item An Introduction to Markov Processes, by Daniel W. Stroock, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item An Introduction to Markov Processes, by Daniel W. Stroock, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
 Summary
 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
 Language
 eng
 Edition
 2nd ed. 2014.
 Extent
 XVII, 203 p.
 Contents

 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
 Isbn
 9783642405235
 Label
 An Introduction to Markov Processes
 Title
 An Introduction to Markov Processes
 Statement of responsibility
 by Daniel W. Stroock
 Language
 eng
 Summary
 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
 http://library.link/vocab/creatorName
 Stroock, Daniel W
 Image bit depth
 0
 LC call number

 QA273.A1274.9
 QA274274.9
 Literary form
 non fiction
 http://library.link/vocab/relatedWorkOrContributorName
 SpringerLink
 Series statement
 Graduate Texts in Mathematics,
 Series volume
 230
 http://library.link/vocab/subjectName

 Mathematics
 Differentiable dynamical systems
 Distribution (Probability theory)
 Mathematics
 Probability Theory and Stochastic Processes
 Dynamical Systems and Ergodic Theory
 Label
 An Introduction to Markov Processes, by Daniel W. Stroock, (electronic resource)
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents
 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
 Dimensions
 unknown
 Edition
 2nd ed. 2014.
 Extent
 XVII, 203 p.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9783642405235
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Other control number
 10.1007/9783642405235
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number
 (DEHe213)9783642405235
 Label
 An Introduction to Markov Processes, by Daniel W. Stroock, (electronic resource)
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents
 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
 Dimensions
 unknown
 Edition
 2nd ed. 2014.
 Extent
 XVII, 203 p.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9783642405235
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Other control number
 10.1007/9783642405235
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number
 (DEHe213)9783642405235
Subject
 Differentiable dynamical systems
 Differentiable dynamical systems
 Distribution (Probability theory)
 Distribution (Probability theory)
 Distribution (Probability theory)
 Dynamical Systems and Ergodic Theory
 Electronic resources
 Mathematics
 Mathematics
 Probability Theory and Stochastic Processes
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