Markov Processes
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Markov Processes
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Author : Daniel T. Gillespie
language : en
Publisher: Elsevier
Release Date : 1991-12-02
Markov Processes written by Daniel T. Gillespie and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-12-02 with Mathematics categories.
Markov process theory is basically an extension of ordinary calculus to accommodate functions whos time evolutions are not entirely deterministic. It is a subject that is becoming increasingly important for many fields of science. This book develops the single-variable theory of both continuous and jump Markov processes in a way that should appeal especially to physicists and chemists at the senior and graduate level. - A self-contained, prgamatic exposition of the needed elements of random variable theory - Logically integrated derviations of the Chapman-Kolmogorov equation, the Kramers-Moyal equations, the Fokker-Planck equations, the Langevin equation, the master equations, and the moment equations - Detailed exposition of Monte Carlo simulation methods, with plots of many numerical examples - Clear treatments of first passages, first exits, and stable state fluctuations and transitions - Carefully drawn applications to Brownian motion, molecular diffusion, and chemical kinetics
Markov Processes And Applications
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Author : Etienne Pardoux
language : en
Publisher: John Wiley & Sons
Release Date : 2008-11-20
Markov Processes And Applications written by Etienne Pardoux and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-20 with Mathematics categories.
"This well-written book provides a clear and accessible treatment of the theory of discrete and continuous-time Markov chains, with an emphasis towards applications. The mathematical treatment is precise and rigorous without superfluous details, and the results are immediately illustrated in illuminating examples. This book will be extremely useful to anybody teaching a course on Markov processes." Jean-François Le Gall, Professor at Université de Paris-Orsay, France. Markov processes is the class of stochastic processes whose past and future are conditionally independent, given their present state. They constitute important models in many applied fields. After an introduction to the Monte Carlo method, this book describes discrete time Markov chains, the Poisson process and continuous time Markov chains. It also presents numerous applications including Markov Chain Monte Carlo, Simulated Annealing, Hidden Markov Models, Annotation and Alignment of Genomic sequences, Control and Filtering, Phylogenetic tree reconstruction and Queuing networks. The last chapter is an introduction to stochastic calculus and mathematical finance. Features include: The Monte Carlo method, discrete time Markov chains, the Poisson process and continuous time jump Markov processes. An introduction to diffusion processes, mathematical finance and stochastic calculus. Applications of Markov processes to various fields, ranging from mathematical biology, to financial engineering and computer science. Numerous exercises and problems with solutions to most of them
General Theory Of Markov Processes
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Author :
language : en
Publisher: Academic Press
Release Date : 1988-11-01
General Theory Of Markov Processes written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-11-01 with Mathematics categories.
General Theory of Markov Processes
Markov Processes
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Author : James R. Kirkwood
language : en
Publisher: CRC Press
Release Date : 2015-02-09
Markov Processes written by James R. Kirkwood and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-09 with Business & Economics categories.
Clear, rigorous, and intuitive, Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic processes and also as a reference for those that want to see detailed proofs of the theorems of Markov processes. It contains copious computational examples that motivate and illustrate the theorems. The text is desi
Continuous Time Markov Processes
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Author : Thomas M. Liggett
language : en
Publisher: American Mathematical Society
Release Date : 2025-08-27
Continuous Time Markov Processes written by Thomas M. Liggett and has been published by American Mathematical Society this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-27 with Mathematics categories.
Markov processes are among the most important stochastic processes for both theory and applications. This book develops the general theory of these processes and applies this theory to various special examples. The initial chapter is devoted to the most important classical example?one-dimensional Brownian motion. This, together with a chapter on continuous time Markov chains, provides the motivation for the general setup based on semigroups and generators. Chapters on stochastic calculus and probabilistic potential theory give an introduction to some of the key areas of application of Brownian motion and its relatives. A chapter on interacting particle systems treats a more recently developed class of Markov processes that have as their origin problems in physics and biology. This is a textbook for a graduate course that can follow one that covers basic probabilistic limit theorems and discrete time processes.
An Introduction To Markov Processes
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Author : Daniel W. Stroock
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-10-14
An Introduction To Markov Processes written by Daniel W. Stroock and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-10-14 with Mathematics categories.
To some extent, it would be accurate to summarize the contents of this book as an intolerably protracted description of what happens when either one raises a transition probability matrix P (i. e. , all entries (P)»j are n- negative and each row of P sums to 1) to higher and higher powers or one exponentiates R(P — I), where R is a diagonal matrix with non-negative entries. Indeed, when it comes right down to it, that is all that is done in this book. However, I, and others of my ilk, would take offense at such a dismissive characterization of the theory of Markov chains and processes with values in a countable state space, and a primary goal of mine in writing this book was to convince its readers that our offense would be warranted. The reason why I, and others of my persuasion, refuse to consider the theory here as no more than a subset of matrix theory is that to do so is to ignore the pervasive role that probability plays throughout. Namely, probability theory provides a model which both motivates and provides a context for what we are doing with these matrices. To wit, even the term "transition probability matrix" lends meaning to an otherwise rather peculiar set of hypotheses to make about a matrix.
Markov Processes And Differential Equations
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Author : Mark I. Freidlin
language : en
Publisher: Springer Science & Business Media
Release Date : 1996-03-28
Markov Processes And Differential Equations written by Mark I. Freidlin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-03-28 with Mathematics categories.
Probabilistic methods can be applied very successfully to a number of asymptotic problems for second-order linear and non-linear partial differential equations. Due to the close connection between the second order differential operators with a non-negative characteristic form on the one hand and Markov processes on the other, many problems in PDE's can be reformulated as problems for corresponding stochastic processes and vice versa. In the present book four classes of problems are considered: - the Dirichlet problem with a small parameter in higher derivatives for differential equations and systems - the averaging principle for stochastic processes and PDE's - homogenization in PDE's and in stochastic processes - wave front propagation for semilinear differential equations and systems. From the probabilistic point of view, the first two topics concern random perturbations of dynamical systems. The third topic, homog- enization, is a natural problem for stochastic processes as well as for PDE's. Wave fronts in semilinear PDE's are interesting examples of pattern formation in reaction-diffusion equations. The text presents new results in probability theory and their applica- tion to the above problems. Various examples help the reader to understand the effects. Prerequisites are knowledge in probability theory and in partial differential equations.
Theory Of Markov Processes
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Author : Evgeniĭ Borisovich Dynkin
language : en
Publisher: Courier Corporation
Release Date : 2006-01-01
Theory Of Markov Processes written by Evgeniĭ Borisovich Dynkin and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-01 with Mathematics categories.
An investigation of the logical foundations of the theory behind Markov random processes, this text explores subprocesses, transition functions, and conditions for boundedness and continuity. Rather than focusing on probability measures individually, the work explores connections between functions. An elementary grasp of the theory of Markov processes is assumed. Starting with a brief survey of relevant concepts and theorems from measure theory, the text investigates operations that permit an inspection of the class of Markov processes corresponding to a given transition function. It advances to the more complicated operations of generating a subprocess, followed by examinations of the construction of Markov processes with given transition functions, the concept of a strictly "Markov process," and the conditions required for boundedness and continuity of a Markov process. Addenda, notes, references, and indexes supplement the text.
The Construction Theory Of Denumerable Markov Processes
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Author : Xiangqun Yang
language : en
Publisher:
Release Date : 1990-12-21
The Construction Theory Of Denumerable Markov Processes written by Xiangqun Yang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-12-21 with Mathematics categories.
Reaches the forefront of research in the construction theory of denumerable Markov processes and gives impetus to the development of probability theory. Introduces Markov processes and their construction; surveys research in the field; and presents the author's original results, which include complete solutions to some important problems, many published here for the first time in English. Complete solutions are given for two key construction problems: birth-death processes and two-sided birth-death processes.
Markov Processes For Stochastic Modeling
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Author : Masaaki Kijima
language : en
Publisher: CRC Press
Release Date : 1997-01-01
Markov Processes For Stochastic Modeling written by Masaaki Kijima and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-01-01 with Mathematics categories.
This book presents an algebraic development of the theory of countable state space Markov chains with discrete and continuous time parameters.