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General Theory Of Markov Processes


General Theory Of Markov Processes
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General Theory Of Markov Processes


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



Statistics Of Random Processes Ii


Statistics Of Random Processes Ii
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Author : Robert Shevilevich Lipt︠s︡er
language : en
Publisher: Springer Science & Business Media
Release Date : 2001

Statistics Of Random Processes Ii written by Robert Shevilevich Lipt︠s︡er 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 2001 with Mathematics categories.


"Written by two renowned experts in the field, the books under review contain a thorough and insightful treatment of the fundamental underpinnings of various aspects of stochastic processes as well as a wide range of applications. Providing clear exposition, deep mathematical results, and superb technical representation, they are masterpieces of the subject of stochastic analysis and nonlinear filtering....These books...will become classics." --SIAM REVIEW



Markov Processes


Markov Processes
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Author : Daniel T. Gillespie
language : en
Publisher: Gulf Professional Publishing
Release Date : 1992

Markov Processes written by Daniel T. Gillespie and has been published by Gulf Professional Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Mathematics categories.


Markov process theory provides a mathematical framework for analyzing the elements of randomness that are involved in most real-world dynamical processes. This introductory text, which requires an understanding of ordinary calculus, develops the concepts and results of random variable theory.



Markov Processes And Potential Theory


Markov Processes And Potential Theory
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Author : Robert McCallum Blumenthal
language : en
Publisher: Courier Corporation
Release Date : 2007-01-01

Markov Processes And Potential Theory written by Robert McCallum Blumenthal and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-01-01 with Mathematics categories.


This graduate-level text explores the relationship between Markov processes and potential theory, in addition to aspects of the theory of additive functionals. Topics include Markov processes, excessive functions, multiplicative functionals and subprocesses, and additive functionals and their potentials. A concluding chapter examines dual processes and potential theory. 1968 edition.



An Introduction To Markov Processes


An Introduction To Markov Processes
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Author : Daniel W. Stroock
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-11-23

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 2004-11-23 with Mathematics categories.


Provides a more accessible introduction than other books on Markov processes by emphasizing the structure of the subject and avoiding sophisticated measure theory Leads the reader to a rigorous understanding of basic theory



Markov Decision Processes With Applications To Finance


Markov Decision Processes With Applications To Finance
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Author : Nicole Bäuerle
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-06

Markov Decision Processes With Applications To Finance written by Nicole Bäuerle 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 2011-06-06 with Mathematics categories.


The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers in both applied probability and finance, and provides exercises (without solutions).



Semi Markov Processes And Reliability


Semi Markov Processes And Reliability
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Author : Nikolaos Limnios
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-02-16

Semi Markov Processes And Reliability written by Nikolaos Limnios 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 2001-02-16 with Technology & Engineering categories.


At first there was the Markov property. The theory of stochastic processes, which can be considered as an exten sion of probability theory, allows the modeling of the evolution of systems through the time. It cannot be properly understood just as pure mathemat ics, separated from the body of experience and examples that have brought it to life. The theory of stochastic processes entered a period of intensive develop ment, which is not finished yet, when the idea of the Markov property was brought in. Not even a serious study of the renewal processes is possible without using the strong tool of Markov processes. The modern theory of Markov processes has its origins in the studies by A. A: Markov (1856-1922) of sequences of experiments "connected in a chain" and in the attempts to describe mathematically the physical phenomenon known as Brownian mo tion. Later, many generalizations (in fact all kinds of weakenings of the Markov property) of Markov type stochastic processes were proposed. Some of them have led to new classes of stochastic processes and useful applications. Let us mention some of them: systems with complete connections [90, 91, 45, 86]; K-dependent Markov processes [44]; semi-Markov processes, and so forth. The semi-Markov processes generalize the renewal processes as well as the Markov jump processes and have numerous applications, especially in relia bility.



Markov Processes Gaussian Processes And Local Times


Markov Processes Gaussian Processes And Local Times
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Author : Michael B. Marcus
language : en
Publisher: Cambridge University Press
Release Date : 2006-07-24

Markov Processes Gaussian Processes And Local Times written by Michael B. Marcus and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-24 with Mathematics categories.


A readable 2006 synthesis of three main areas in the modern theory of stochastic processes.



Markov Processes


Markov Processes
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Author : E. B. Dynkin
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Markov Processes written by E. B. Dynkin 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 2012-12-06 with Mathematics categories.


The modem theory of Markov processes has its origins in the studies of A. A. MARKOV (1906-1907) on sequences of experiments "connected in a chain" and in the attempts to describe mathematically the physical phenomenon known as Brownian motion (L. BACHELlER 1900, A. EIN STEIN 1905). The first correct mathematical construction of a Markov process with continuous trajectories was given by N. WIENER in 1923. (This process is often called the Wiener process.) The general theory of Markov processes was developed in the 1930's and 1940's by A. N. KOL MOGOROV, W. FELLER, W. DOEBLlN, P. LEVY, J. L. DOOB, and others. During the past ten years the theory of Markov processes has entered a new period of intensive development. The methods of the theory of semigroups of linear operators made possible further progress in the classification of Markov processes by their infinitesimal characteristics. The broad classes of Markov processes with continuous trajectories be came the main object of study. The connections between Markov pro cesses and classical analysis were further developed. It has become possible not only to apply the results and methods of analysis to the problems of probability theory, but also to investigate analytic problems using probabilistic methods. Remarkable new connections between Markov processes and potential theory were revealed. The foundations of the theory were reviewed critically: the new concept of strong Markov process acquired for the whole theory of Markov processes great importance.



Theory Of Markov Processes


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.