Stochastic Processes With R

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Introduction to Stochastic Processes with R

Robert P. Dobrow
Introduction to Stochastic Processes with R Book PDF

Author : Robert P. Dobrow
Publisher : John Wiley & Sons
Page : 503 pages
File Size : 45,6 Mb
Release : 2016-03-07
Category : Mathematics
ISBN : 9781118740651

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Introduction to Stochastic Processes with R by Robert P. Dobrow Pdf

An introduction to stochastic processes through the use of R Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The use of simulation, by means of the popular statistical software R, makes theoretical results come alive with practical, hands-on demonstrations. Written by a highly-qualified expert in the field, the author presents numerous examples from a wide array of disciplines, which are used to illustrate concepts and highlight computational and theoretical results. Developing readers’ problem-solving skills and mathematical maturity, Introduction to Stochastic Processes with R features: More than 200 examples and 600 end-of-chapter exercises A tutorial for getting started with R, and appendices that contain review material in probability and matrix algebra Discussions of many timely and stimulating topics including Markov chain Monte Carlo, random walk on graphs, card shuffling, Black–Scholes options pricing, applications in biology and genetics, cryptography, martingales, and stochastic calculus Introductions to mathematics as needed in order to suit readers at many mathematical levels A companion web site that includes relevant data files as well as all R code and scripts used throughout the book Introduction to Stochastic Processes with R is an ideal textbook for an introductory course in stochastic processes. The book is aimed at undergraduate and beginning graduate-level students in the science, technology, engineering, and mathematics disciplines. The book is also an excellent reference for applied mathematicians and statisticians who are interested in a review of the topic.

Stochastic Processes with R

Olga Korosteleva
Stochastic Processes with R Book PDF

Author : Olga Korosteleva
Publisher : CRC Press
Page : 180 pages
File Size : 54,5 Mb
Release : 2022-02-14
Category : Mathematics
ISBN : 9781000537376

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Stochastic Processes with R by Olga Korosteleva Pdf

Stochastic Processes with R: An Introduction cuts through the heavy theory that is present in most courses on random processes and serves as practical guide to simulated trajectories and real-life applications for stochastic processes. The light yet detailed text provides a solid foundation that is an ideal companion for undergraduate statistics students looking to familiarize themselves with stochastic processes before going on to more advanced courses. Key Features Provides complete R codes for all simulations and calculations Substantial scientific or popular applications of each process with occasional statistical analysis Helpful definitions and examples are provided for each process End of chapter exercises cover theoretical applications and practice calculations

Essentials of Stochastic Processes

Richard Durrett
Essentials of Stochastic Processes Book PDF

Author : Richard Durrett
Publisher : Springer
Page : 282 pages
File Size : 40,8 Mb
Release : 2016-11-07
Category : Mathematics
ISBN : 9783319456140

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Essentials of Stochastic Processes by Richard Durrett Pdf

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.

Stochastic Processes

Robert G. Gallager
Stochastic Processes Book PDF

Author : Robert G. Gallager
Publisher : Cambridge University Press
Page : 559 pages
File Size : 44,8 Mb
Release : 2013-12-12
Category : Business & Economics
ISBN : 9781107039759

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Stochastic Processes by Robert G. Gallager Pdf

The definitive textbook on stochastic processes, written by one of the world's leading information theorists, covering both theory and applications.

Basics of Applied Stochastic Processes

Richard Serfozo
Basics of Applied Stochastic Processes Book PDF

Author : Richard Serfozo
Publisher : Springer Science & Business Media
Page : 452 pages
File Size : 48,7 Mb
Release : 2009-01-24
Category : Mathematics
ISBN : 9783540893325

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Basics of Applied Stochastic Processes by Richard Serfozo Pdf

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.

Introduction to Stochastic Processes

Paul G. Hoel,Sidney C. Port,Charles J. Stone
Introduction to Stochastic Processes Book PDF

Author : Paul G. Hoel,Sidney C. Port,Charles J. Stone
Publisher : Waveland Press
Page : 212 pages
File Size : 48,7 Mb
Release : 1986-12-01
Category : Mathematics
ISBN : 9781478608998

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Introduction to Stochastic Processes by Paul G. Hoel,Sidney C. Port,Charles J. Stone Pdf

An excellent introduction for computer scientists and electrical and electronics engineers who would like to have a good, basic understanding of stochastic processes! This clearly written book responds to the increasing interest in the study of systems that vary in time in a random manner. It presents an introductory account of some of the important topics in the theory of the mathematical models of such systems. The selected topics are conceptually interesting and have fruitful application in various branches of science and technology.

Stochastic Processes

Peter Watts Jones,Peter Smith
Stochastic Processes Book PDF

Author : Peter Watts Jones,Peter Smith
Publisher : CRC Press
Page : 255 pages
File Size : 48,7 Mb
Release : 2017-10-30
Category : Mathematics
ISBN : 9781498778121

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Stochastic Processes by Peter Watts Jones,Peter Smith Pdf

Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments, where processes evolve over time. The text begins with a review of relevant fundamental probability. It then covers gambling problems, random walks, and Markov chains. The authors go on to discuss random processes continuous in time, including Poisson, birth and death processes, and general population models, and present an extended discussion on the analysis of associated stationary processes in queues. The book also explores reliability and other random processes, such as branching, martingales, and simple epidemics. A new chapter describing Brownian motion, where the outcomes are continuously observed over continuous time, is included. Further applications, worked examples and problems, and biographical details have been added to this edition. Much of the text has been reworked. The appendix contains key results in probability for reference. This concise, updated book makes the material accessible, highlighting simple applications and examples. A solutions manual with fully worked answers of all end-of-chapter problems, and Mathematica® and R programs illustrating many processes discussed in the book, can be downloaded from crcpress.com.

Simulation and Inference for Stochastic Processes with YUIMA

Stefano M. Iacus,Nakahiro Yoshida
Simulation and Inference for Stochastic Processes with YUIMA Book PDF

Author : Stefano M. Iacus,Nakahiro Yoshida
Publisher : Springer
Page : 268 pages
File Size : 54,9 Mb
Release : 2018-06-01
Category : Computers
ISBN : 9783319555690

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Simulation and Inference for Stochastic Processes with YUIMA by Stefano M. Iacus,Nakahiro Yoshida Pdf

The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes. The package performs various central statistical analyses such as quasi maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on. YUIMA also supports stochastic numerical analysis by fast computation of the expected value of functionals of stochastic processes through automatic asymptotic expansion by means of the Malliavin calculus. All models can be multidimensional, multiparametric or non parametric.The book explains briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation experiments and applications to real data. Although these processes have been originally proposed in physics and more recently in finance, they are becoming popular also in biology due to the fact the time course experimental data are now available. The YUIMA package, available on CRAN, can be freely downloaded and this companion book will make the user able to start his or her analysis from the first page.

Discrete Stochastic Processes

Robert G. Gallager
Discrete Stochastic Processes Book PDF

Author : Robert G. Gallager
Publisher : Springer Science & Business Media
Page : 280 pages
File Size : 43,8 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461523291

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Discrete Stochastic Processes by Robert G. Gallager Pdf

Stochastic processes are found in probabilistic systems that evolve with time. Discrete stochastic processes change by only integer time steps (for some time scale), or are characterized by discrete occurrences at arbitrary times. Discrete Stochastic Processes helps the reader develop the understanding and intuition necessary to apply stochastic process theory in engineering, science and operations research. The book approaches the subject via many simple examples which build insight into the structure of stochastic processes and the general effect of these phenomena in real systems. The book presents mathematical ideas without recourse to measure theory, using only minimal mathematical analysis. In the proofs and explanations, clarity is favored over formal rigor, and simplicity over generality. Numerous examples are given to show how results fail to hold when all the conditions are not satisfied. Audience: An excellent textbook for a graduate level course in engineering and operations research. Also an invaluable reference for all those requiring a deeper understanding of the subject.

Stochastic Processes and Applications

Grigorios A. Pavliotis
Stochastic Processes and Applications Book PDF

Author : Grigorios A. Pavliotis
Publisher : Springer
Page : 345 pages
File Size : 55,8 Mb
Release : 2014-11-19
Category : Mathematics
ISBN : 9781493913237

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Stochastic Processes and Applications by Grigorios A. Pavliotis Pdf

This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical methods, although numerical methods and statistical inference methodologies for studying diffusion processes are also presented. The goal is the development of techniques that are applicable to a wide variety of stochastic models that appear in physics, chemistry and other natural sciences. Applications such as stochastic resonance, Brownian motion in periodic potentials and Brownian motors are studied and the connection between diffusion processes and time-dependent statistical mechanics is elucidated. The book contains a large number of illustrations, examples, and exercises. It will be useful for graduate-level courses on stochastic processes for students in applied mathematics, physics and engineering. Many of the topics covered in this book (reversible diffusions, convergence to equilibrium for diffusion processes, inference methods for stochastic differential equations, derivation of the generalized Langevin equation, exit time problems) cannot be easily found in textbook form and will be useful to both researchers and students interested in the applications of stochastic processes.

The Theory of Stochastic Processes I

Iosif I. Gikhman,Anatoli V. Skorokhod
The Theory of Stochastic Processes I Book PDF

Author : Iosif I. Gikhman,Anatoli V. Skorokhod
Publisher : Springer
Page : 587 pages
File Size : 46,5 Mb
Release : 2015-03-30
Category : Mathematics
ISBN : 9783642619434

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The Theory of Stochastic Processes I by Iosif I. Gikhman,Anatoli V. Skorokhod Pdf

From the Reviews: "Gihman and Skorohod have done an excellent job of presenting the theory in its present state of rich imperfection." --D.W. Stroock, Bulletin of the American Mathematical Society, 1980

Introduction to Stochastic Models

Roe Goodman
Introduction to Stochastic Models Book PDF

Author : Roe Goodman
Publisher : Courier Corporation
Page : 370 pages
File Size : 53,7 Mb
Release : 2006-01-01
Category : Mathematics
ISBN : 9780486450377

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Introduction to Stochastic Models by Roe Goodman Pdf

Newly revised by the author, this undergraduate-level text introduces the mathematical theory of probability and stochastic processes. Using both computer simulations and mathematical models of random events, it comprises numerous applications to the physical and biological sciences, engineering, and computer science. Subjects include sample spaces, probabilities distributions and expectations of random variables, conditional expectations, Markov chains, and the Poisson process. Additional topics encompass continuous-time stochastic processes, birth and death processes, steady-state probabilities, general queuing systems, and renewal processes. Each section features worked examples, and exercises appear at the end of each chapter, with numerical solutions at the back of the book. Suggestions for further reading in stochastic processes, simulation, and various applications also appear at the end.

Probability Theory and Stochastic Processes

Pierre Brémaud
Probability Theory and Stochastic Processes Book PDF

Author : Pierre Brémaud
Publisher : Springer Nature
Page : 713 pages
File Size : 40,6 Mb
Release : 2020-04-07
Category : Mathematics
ISBN : 9783030401832

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Probability Theory and Stochastic Processes by Pierre Brémaud Pdf

The ultimate objective of this book is to present a panoramic view of the main stochastic processes which have an impact on applications, with complete proofs and exercises. Random processes play a central role in the applied sciences, including operations research, insurance, finance, biology, physics, computer and communications networks, and signal processing. In order to help the reader to reach a level of technical autonomy sufficient to understand the presented models, this book includes a reasonable dose of probability theory. On the other hand, the study of stochastic processes gives an opportunity to apply the main theoretical results of probability theory beyond classroom examples and in a non-trivial manner that makes this discipline look more attractive to the applications-oriented student. One can distinguish three parts of this book. The first four chapters are about probability theory, Chapters 5 to 8 concern random sequences, or discrete-time stochastic processes, and the rest of the book focuses on stochastic processes and point processes. There is sufficient modularity for the instructor or the self-teaching reader to design a course or a study program adapted to her/his specific needs. This book is in a large measure self-contained.

Introduction to Stochastic Processes

Gregory F. Lawler
Introduction to Stochastic Processes Book PDF

Author : Gregory F. Lawler
Publisher : CRC Press
Page : 249 pages
File Size : 48,8 Mb
Release : 2018-10-03
Category : Mathematics
ISBN : 9781482286113

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Introduction to Stochastic Processes by Gregory F. Lawler Pdf

Emphasizing fundamental mathematical ideas rather than proofs, Introduction to Stochastic Processes, Second Edition provides quick access to important foundations of probability theory applicable to problems in many fields. Assuming that you have a reasonable level of computer literacy, the ability to write simple programs, and the access to software for linear algebra computations, the author approaches the problems and theorems with a focus on stochastic processes evolving with time, rather than a particular emphasis on measure theory. For those lacking in exposure to linear differential and difference equations, the author begins with a brief introduction to these concepts. He proceeds to discuss Markov chains, optimal stopping, martingales, and Brownian motion. The book concludes with a chapter on stochastic integration. The author supplies many basic, general examples and provides exercises at the end of each chapter. New to the Second Edition: Expanded chapter on stochastic integration that introduces modern mathematical finance Introduction of Girsanov transformation and the Feynman-Kac formula Expanded discussion of Itô's formula and the Black-Scholes formula for pricing options New topics such as Doob's maximal inequality and a discussion on self similarity in the chapter on Brownian motion Applicable to the fields of mathematics, statistics, and engineering as well as computer science, economics, business, biological science, psychology, and engineering, this concise introduction is an excellent resource both for students and professionals.

Stochastic Processes for Physicists

Kurt Jacobs
Stochastic Processes for Physicists Book PDF

Author : Kurt Jacobs
Publisher : Cambridge University Press
Page : 203 pages
File Size : 47,6 Mb
Release : 2010-02-18
Category : Science
ISBN : 9781139486798

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Stochastic Processes for Physicists by Kurt Jacobs Pdf

Stochastic processes are an essential part of numerous branches of physics, as well as in biology, chemistry, and finance. This textbook provides a solid understanding of stochastic processes and stochastic calculus in physics, without the need for measure theory. In avoiding measure theory, this textbook gives readers the tools necessary to use stochastic methods in research with a minimum of mathematical background. Coverage of the more exotic Levy processes is included, as is a concise account of numerical methods for simulating stochastic systems driven by Gaussian noise. The book concludes with a non-technical introduction to the concepts and jargon of measure-theoretic probability theory. With over 70 exercises, this textbook is an easily accessible introduction to stochastic processes and their applications, as well as methods for numerical simulation, for graduate students and researchers in physics.