First Passage Times and Outer Analysis of Continuous Parameter Markov Chains PDF Download
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Author: I. MacNeill
Publisher:
ISBN:
Category :
Languages : en
Pages : 16
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Book Description
Two methods are discussed of computing first passage times for a finite state, continuous time parameter Markov chain. One of the methods involves a system of differential equations and the other is the Laplace transform technique. Other analyses involve the transition probability matrix and the steady state distribution. Several techniques for making computations are given and an example is worked. A problem is solved which was presented by one of the agencies served under the Joint Services Advisory Group program. (Author).
Author: I. MacNeill
Publisher:
ISBN:
Category :
Languages : en
Pages : 16
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Book Description
Two methods are discussed of computing first passage times for a finite state, continuous time parameter Markov chain. One of the methods involves a system of differential equations and the other is the Laplace transform technique. Other analyses involve the transition probability matrix and the steady state distribution. Several techniques for making computations are given and an example is worked. A problem is solved which was presented by one of the agencies served under the Joint Services Advisory Group program. (Author).
Author: Ian B. MacNeill
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 12
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Book Description
Author: Hal Caswell
Publisher: Springer
ISBN: 3030105342
Category : Social Science
Languages : en
Pages : 308
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Book Description
This open access book shows how to use sensitivity analysis in demography. It presents new methods for individuals, cohorts, and populations, with applications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases. Readers will discover results on the sensitivity of statistics of longevity, life disparity, occupancy times, the net reproductive rate, and statistics of Markov chain models in demography. They will also see applications of sensitivity analysis to population growth rates, stable population structures, reproductive value, equilibria under immigration and nonlinearity, and population cycles. Individual stochasticity is a theme throughout, with a focus that goes beyond expected values to include variances in demographic outcomes. The calculations are easily and accurately implemented in matrix-oriented programming languages such as Matlab or R. Sensitivity analysis will help readers create models to predict the effect of future changes, to evaluate policy effects, and to identify possible evolutionary responses to the environment. Complete with many examples of the application, the book will be of interest to researchers and graduate students in human demography and population biology. The material will also appeal to those in mathematical biology and applied mathematics.
Author: R. Syski
Publisher: IOS Press
ISBN: 9789051990607
Category : Computers
Languages : en
Pages : 564
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Book Description
This book is a survey of work on passage times in stable Markov chains with a discrete state space and a continuous time. Passage times have been investigated since early days of probability theory and its applications. The best known example is the first entrance time to a set, which embraces waiting times, busy periods, absorption problems, extinction phenomena, etc. Another example of great interest is the last exit time from a set. The book presents a unifying treatment of passage times, written in a systematic manner and based on modern developments. The appropriate unifying framework is provided by probabilistic potential theory, and the results presented in the text are interpreted from this point of view. In particular, the crucial role of the Dirichlet problem and the Poisson equation is stressed. The work is addressed to applied probalilists, and to those who are interested in applications of probabilistic methods in their own areas of interest. The level of presentation is that of a graduate text in applied stochastic processes. Hence, clarity of presentation takes precedence over secondary mathematical details whenever no serious harm may be expected. Advanced concepts described in the text gain nowadays growing acceptance in applied fields, and it is hoped that this work will serve as an useful introduction. Abstracted by Mathematical Reviews, issue 94c
Author: William J. Anderson
Publisher: Springer Science & Business Media
ISBN: 1461230381
Category : Mathematics
Languages : en
Pages : 367
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Book Description
Continuous time parameter Markov chains have been useful for modeling various random phenomena occurring in queueing theory, genetics, demography, epidemiology, and competing populations. This is the first book about those aspects of the theory of continuous time Markov chains which are useful in applications to such areas. It studies continuous time Markov chains through the transition function and corresponding q-matrix, rather than sample paths. An extensive discussion of birth and death processes, including the Stieltjes moment problem, and the Karlin-McGregor method of solution of the birth and death processes and multidimensional population processes is included, and there is an extensive bibliography. Virtually all of this material is appearing in book form for the first time.
Author: Nicolas Privault
Publisher: Springer
ISBN: 9811306591
Category : Mathematics
Languages : en
Pages : 379
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Book Description
This book provides an undergraduate-level introduction to discrete and continuous-time Markov chains and their applications, with a particular focus on the first step analysis technique and its applications to average hitting times and ruin probabilities. It also discusses classical topics such as recurrence and transience, stationary and limiting distributions, as well as branching processes. It first examines in detail two important examples (gambling processes and random walks) before presenting the general theory itself in the subsequent chapters. It also provides an introduction to discrete-time martingales and their relation to ruin probabilities and mean exit times, together with a chapter on spatial Poisson processes. The concepts presented are illustrated by examples, 138 exercises and 9 problems with their solutions.
Author: Kai Lai Chung
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 30
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Book Description
Author: Kai Lai Chung
Publisher: Springer Science & Business Media
ISBN: 3642620159
Category : Mathematics
Languages : en
Pages : 312
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Book Description
From the reviews: J. Neveu, 1962 in Zentralblatt fr Mathematik, 92. Band Heft 2, p. 343: "Ce livre crit par l'un des plus minents spcialistes en la matire, est un expos trs dtaill de la thorie des processus de Markov dfinis sur un espace dnombrable d'tats et homognes dans le temps (chaines stationnaires de Markov)." N. Jain, 2008 in Selected Works of Kai Lai Chung, edited by Farid AitSahlia (University of Florida, USA), Elton Hsu (Northwestern University, USA), & Ruth Williams (University of California-San Diego, USA), Chapter 1, p. 15: "This monograph deals with countable state Markov chains in both discrete time (Part I) and continuous time (Part II). ... Much of Kai Lai's fundamental work in the field is included in this monograph. Here, for the first time, Kai Lai gave a systematic exposition of the subject which includes classification of states, ratio ergodic theorems, and limit theorems for functionals of the chain."
Author: Thomas Milton Liggett
Publisher: American Mathematical Soc.
ISBN: 0821849492
Category : Mathematics
Languages : en
Pages : 290
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Book Description
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.
Author: Marius Iosifescu
Publisher: Courier Corporation
ISBN: 0486150585
Category : Mathematics
Languages : en
Pages : 305
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Book Description
A self-contained treatment of finite Markov chains and processes, this text covers both theory and applications. Author Marius Iosifescu, vice president of the Romanian Academy and director of its Center for Mathematical Statistics, begins with a review of relevant aspects of probability theory and linear algebra. Experienced readers may start with the second chapter, a treatment of fundamental concepts of homogeneous finite Markov chain theory that offers examples of applicable models. The text advances to studies of two basic types of homogeneous finite Markov chains: absorbing and ergodic chains. A complete study of the general properties of homogeneous chains follows. Succeeding chapters examine the fundamental role of homogeneous infinite Markov chains in mathematical modeling employed in the fields of psychology and genetics; the basics of nonhomogeneous finite Markov chain theory; and a study of Markovian dependence in continuous time, which constitutes an elementary introduction to the study of continuous parameter stochastic processes.
