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Excursions of Markov Processes

Excursions of Markov Processes PDF Author: Robert M. Blumenthal
Publisher: Springer Science & Business Media
ISBN: 1468494120
Category : Mathematics
Languages : en
Pages : 287

Book Description
Let {Xti t ~ O} be a Markov process in Rl, and break up the path X t into (random) component pieces consisting of the zero set ({ tlX = O}) and t the "excursions away from 0," that is pieces of path X. : T ::5 s ::5 t, with Xr- = X = 0, but X. 1= 0 for T

Excursions of Markov Processes

Excursions of Markov Processes PDF Author: Robert M. Blumenthal
Publisher: Springer Science & Business Media
ISBN: 1468494120
Category : Mathematics
Languages : en
Pages : 287

Book Description
Let {Xti t ~ O} be a Markov process in Rl, and break up the path X t into (random) component pieces consisting of the zero set ({ tlX = O}) and t the "excursions away from 0," that is pieces of path X. : T ::5 s ::5 t, with Xr- = X = 0, but X. 1= 0 for T

An excursion into Markov chains

An excursion into Markov chains PDF Author: Marco Ferrante
Publisher: Springer
ISBN: 9783319128337
Category : Mathematics
Languages : en
Pages : 250

Book Description
This textbook will present, in a rigorous way, the basic theory of the discrete-time and the continuous-time Markov chains, along with many examples and solved problems. For both the topics a simple model, the Random Walk and the Poisson Process respectively, will be used to anticipate and illustrate the most interesting concepts rigorously defined in the following sections. A great attention will be paid to the applications of the theory of the Markov chains and many classical as well as new results will be faced in the book. This textbook is intended for a basic course on stochastic processes at an advanced undergraduate level and the background needed will be a first course in probability theory. A big emphasis is given to the computational approach and to simulations.

Essentials of Stochastic Processes

Essentials of Stochastic Processes PDF Author: Richard Durrett
Publisher: Springer
ISBN: 3319456148
Category : Mathematics
Languages : en
Pages : 282

Book Description
Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatment of other topics useful for applications has been expanded. In addition, the ordering of topics has been improved; for example, the difficult subject of martingales is delayed until its usefulness can be applied in the treatment of mathematical finance.

Non-negative Matrices and Markov Chains

Non-negative Matrices and Markov Chains PDF Author: E. Seneta
Publisher: Springer Science & Business Media
ISBN: 0387327924
Category : Mathematics
Languages : en
Pages : 295

Book Description
Since its inception by Perron and Frobenius, the theory of non-negative matrices has developed enormously and is now being used and extended in applied fields of study as diverse as probability theory, numerical analysis, demography, mathematical economics, and dynamic programming, while its development is still proceeding rapidly as a branch of pure mathematics in its own right. While there are books which cover this or that aspect of the theory, it is nevertheless not uncommon for workers in one or another branch of its development to be unaware of what is known in other branches, even though there is often formal overlap. One of the purposes of this book is to relate several aspects of the theory, insofar as this is possible. The author hopes that the book will be useful to mathematicians; but in particular to the workers in applied fields, so the mathematics has been kept as simple as could be managed. The mathematical requisites for reading it are: some knowledge of real-variable theory, and matrix theory; and a little knowledge of complex-variable; the emphasis is on real-variable methods. (There is only one part of the book, the second part of 55.5, which is of rather specialist interest, and requires deeper knowledge.) Appendices provide brief expositions of those areas of mathematics needed which may be less g- erally known to the average reader.

Markov Chains and Dependability Theory

Markov Chains and Dependability Theory PDF Author: Gerardo Rubino
Publisher: Cambridge University Press
ISBN: 1107007577
Category : Business & Economics
Languages : en
Pages : 287

Book Description
Covers fundamental and applied results of Markov chain analysis for the evaluation of dependability metrics, for graduate students and researchers.

Markov Paths, Loops and Fields

Markov Paths, Loops and Fields PDF Author: Yves Le Jan
Publisher: Springer Science & Business Media
ISBN: 3642212158
Category : Mathematics
Languages : en
Pages : 128

Book Description
The purpose of these notes is to explore some simple relations between Markovian path and loop measures, the Poissonian ensembles of loops they determine, their occupation fields, uniform spanning trees, determinants, and Gaussian Markov fields such as the free field. These relations are first studied in complete generality for the finite discrete setting, then partly generalized to specific examples in infinite and continuous spaces.

Selected Works Of Kai Lai Chung

Selected Works Of Kai Lai Chung PDF Author: Elton P Hsu
Publisher: World Scientific
ISBN: 9814470147
Category : Mathematics
Languages : en
Pages : 847

Book Description
This unique volume presents a collection of the extensive journal publications written by Kai Lai Chung over a span of 70-odd years. It was produced to celebrate his 90th birthday. The selection is only a subset of the many contributions that he made throughout his prolific career. Another volume, Chance and Choice, published by World Scientific in 2004, contains yet another subset, with four articles in common with this volume. Kai Lai Chung's research contributions have had a major influence on several areas in probability. Among his most significant works are those related to sums of independent random variables, Markov chains, time reversal of Markov processes, probabilistic potential theory, Brownian excursions, and gauge theorems for the Schrödinger equation.As Kai Lai Chung's contributions spawned critical new developments, this volume also contains retrospective and perspective views provided by collaborators and other authors who themselves advanced the areas of probability and mathematics.

Markov Chains

Markov Chains PDF Author: J. R. Norris
Publisher: Cambridge University Press
ISBN: 9780521633963
Category : Mathematics
Languages : en
Pages : 260

Book Description
Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov chains and quickly develops a coherent and rigorous theory whilst showing also how actually to apply it. Both discrete-time and continuous-time chains are studied. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and exercises and examples drawn both from theory and practice. It will therefore be an ideal text either for elementary courses on random processes or those that are more oriented towards applications.

Basics of Applied Stochastic Processes

Basics of Applied Stochastic Processes PDF Author: Richard Serfozo
Publisher: Springer Science & Business Media
ISBN: 3540893326
Category : Mathematics
Languages : en
Pages : 452

Book Description
Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Markov chains in discrete and continuous time, renewal and regenerative processes, Poisson processes, and Brownian motion. This volume gives an in-depth description of the structure and basic properties of these stochastic processes. A main focus is on equilibrium distributions, strong laws of large numbers, and ordinary and functional central limit theorems for cost and performance parameters. Although these results differ for various processes, they have a common trait of being limit theorems for processes with regenerative increments. Extensive examples and exercises show how to formulate stochastic models of systems as functions of a system’s data and dynamics, and how to represent and analyze cost and performance measures. Topics include stochastic networks, spatial and space-time Poisson processes, queueing, reversible processes, simulation, Brownian approximations, and varied Markovian models. The technical level of the volume is between that of introductory texts that focus on highlights of applied stochastic processes, and advanced texts that focus on theoretical aspects of processes.

Stochastic Processes in Genetics and Evolution

Stochastic Processes in Genetics and Evolution PDF Author: Charles J. Mode
Publisher: World Scientific
ISBN: 9814350680
Category : Mathematics
Languages : en
Pages : 695

Book Description
Prologue; Acknowledgments; Contents; 1. An Introduction to Mathematical Probability with Applications in Mendelian Genetics; 1.1 Introduction; 1.2 Mathematical Probability in Mendelian Genetics; 1.3 Examples of Finite Probability Spaces; Example 1.3.1: An Equal Frequency Model; Example 1.3.2: Partitions of an Abstract Set; Example 1.3.3: A Deterministic Case; Example 1.3.4: Inheritance of Eye Color and Sex; 1.4 Elementary Combinatorial Analysis; 1.5 The Binomial Distribution; Example 1.5.1: Distribution of Boys and Girls in Families of Size N.