Introduction To Stochastic Processes
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Introduction To Stochastic Processes
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Author : Paul G. Hoel
language : en
Publisher: Waveland Press
Release Date : 1986-12-01
Introduction To Stochastic Processes written by Paul G. Hoel and has been published by Waveland Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986-12-01 with Mathematics categories.
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.
An Introduction To Stochastic Processes
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Author : M. S. Bartlett
language : en
Publisher: CUP Archive
Release Date : 1978
An Introduction To Stochastic Processes written by M. S. Bartlett and has been published by CUP Archive this book supported file pdf, txt, epub, kindle and other format this book has been release on 1978 with Mathematics categories.
Random sequences; Processes in continuous time; Miscellaneous statistical applications; Limiting stochastic operations; Stationary processes; Prediction and communication theory; The statistical analysis of stochastic processes; Correlation analysis of time-series.
An Introduction To Stochastic Processes
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Author : Edward P.C. Kao
language : en
Publisher: Courier Dover Publications
Release Date : 2019-12-18
An Introduction To Stochastic Processes written by Edward P.C. Kao and has been published by Courier Dover Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-18 with Computers categories.
This incorporation of computer use into teaching and learning stochastic processes takes an applications- and computer-oriented approach rather than a mathematically rigorous approach. Solutions Manual available to instructors upon request. 1997 edition.
An Introduction To Stochastic Modeling
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Author : Howard M. Taylor
language : en
Publisher: Academic Press
Release Date : 2014-05-10
An Introduction To Stochastic Modeling written by Howard M. Taylor and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Mathematics categories.
An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.
An Introduction To Stochastic Processes With Applications To Biology
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Author : Linda J. S. Allen
language : en
Publisher: Prentice Hall
Release Date : 2003
An Introduction To Stochastic Processes With Applications To Biology written by Linda J. S. Allen and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Mathematics categories.
Plenty of examples, diagrams, and figures take readers step-by-step through well-known classical biological models to ensure complete understanding of stochastic formulation. Probability, Markov Chains, discrete time branching processes, population genetics, and birth and death chains. For biologists and other professionals who want a comprehensive, easy-to-follow introduction to stochastic formulation as it pertains to biology.
An Introduction To Stochastic Modeling
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Author : Mark Pinsky
language : en
Publisher: Academic Press
Release Date : 2010-11-18
An Introduction To Stochastic Modeling written by Mark Pinsky and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-18 with Mathematics categories.
Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, Introduction to Stochastic Modeling, Fourth Edition, bridges the gap between basic probability and an intermediate level course in stochastic processes. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of simple stochastic analysis to realistic problems. New to this edition: - Realistic applications from a variety of disciplines integrated throughout the text, including more biological applications - Plentiful, completely updated problems - Completely updated and reorganized end-of-chapter exercise sets, 250 exercises with answers - New chapters of stochastic differential equations and Brownian motion and related processes - Additional sections on Martingale and Poisson process - Realistic applications from a variety of disciplines integrated throughout the text - Extensive end of chapter exercises sets, 250 with answers - Chapter 1-9 of the new edition are identical to the previous edition - New! Chapter 10 - Random Evolutions - New! Chapter 11- Characteristic functions and Their Applications
Introduction To Stochastic Processes Second Edition
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Author : Gregory F. Lawler
language : en
Publisher: CRC Press
Release Date : 2006-05-16
Introduction To Stochastic Processes Second Edition written by Gregory F. Lawler and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-16 with Mathematics categories.
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.
Brownian Motion
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Author : René L. Schilling
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2014-08-22
Brownian Motion written by René L. Schilling and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-22 with Mathematics categories.
Brownian motion is one of the most important stochastic processes in continuous time and with continuous state space. Within the realm of stochastic processes, Brownian motion is at the intersection of Gaussian processes, martingales, Markov processes, diffusions and random fractals, and it has influenced the study of these topics. Its central position within mathematics is matched by numerous applications in science, engineering and mathematical finance. Often textbooks on probability theory cover, if at all, Brownian motion only briefly. On the other hand, there is a considerable gap to more specialized texts on Brownian motion which is not so easy to overcome for the novice. The authors’ aim was to write a book which can be used as an introduction to Brownian motion and stochastic calculus, and as a first course in continuous-time and continuous-state Markov processes. They also wanted to have a text which would be both a readily accessible mathematical back-up for contemporary applications (such as mathematical finance) and a foundation to get easy access to advanced monographs. This textbook, tailored to the needs of graduate and advanced undergraduate students, covers Brownian motion, starting from its elementary properties, certain distributional aspects, path properties, and leading to stochastic calculus based on Brownian motion. It also includes numerical recipes for the simulation of Brownian motion.
Introduction To Stochastic Processes
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Author : Erhan Cinlar
language : en
Publisher: Courier Corporation
Release Date : 2013-02-20
Introduction To Stochastic Processes written by Erhan Cinlar and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-20 with Mathematics categories.
Clear presentation employs methods that recognize computer-related aspects of theory. Topics include expectations and independence, Bernoulli processes and sums of independent random variables, Markov chains, renewal theory, more. 1975 edition.
Introduction To Stochastic Processes
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Author : Mu-fa Chen
language : en
Publisher: World Scientific
Release Date : 2021-05-25
Introduction To Stochastic Processes written by Mu-fa Chen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-25 with Mathematics categories.
The objective of this book is to introduce the elements of stochastic processes in a rather concise manner where we present the two most important parts — Markov chains and stochastic analysis. The readers are led directly to the core of the main topics to be treated in the context. Further details and additional materials are left to a section containing abundant exercises for further reading and studying.In the part on Markov chains, the focus is on the ergodicity. By using the minimal nonnegative solution method, we deal with the recurrence and various types of ergodicity. This is done step by step, from finite state spaces to denumerable state spaces, and from discrete time to continuous time. The methods of proofs adopt modern techniques, such as coupling and duality methods. Some very new results are included, such as the estimate of the spectral gap. The structure and proofs in the first part are rather different from other existing textbooks on Markov chains.In the part on stochastic analysis, we cover the martingale theory and Brownian motions, the stochastic integral and stochastic differential equations with emphasis on one dimension, and the multidimensional stochastic integral and stochastic equation based on semimartingales. We introduce three important topics here: the Feynman-Kac formula, random time transform and Girsanov transform. As an essential application of the probability theory in classical mathematics, we also deal with the famous Brunn-Minkowski inequality in convex geometry.This book also features modern probability theory that is used in different fields, such as MCMC, or even deterministic areas: convex geometry and number theory. It provides a new and direct routine for students going through the classical Markov chains to the modern stochastic analysis.