Introduction To Stochastic Models
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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 Modeling
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Author : Mark Pinsky
language : en
Publisher: Academic Press
Release Date : 2011
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 2011 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 Models
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Author : Roe Goodman
language : en
Publisher: Courier Corporation
Release Date : 2006-01-01
Introduction To Stochastic Models written by Roe Goodman 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.
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.
An Introduction To Stochastic Modeling Student Solutions Manual E Only
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Author : Mark Pinsky
language : en
Publisher: Academic Press
Release Date : 2011-03-30
An Introduction To Stochastic Modeling Student Solutions Manual E Only 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 2011-03-30 with Mathematics categories.
An Introduction to Stochastic Modeling, Student Solutions Manual (e-only)
Introduction To Stochastic Models
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Author : Marius Iosifescu
language : en
Publisher: John Wiley & Sons
Release Date : 2013-03-04
Introduction To Stochastic Models written by Marius Iosifescu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-04 with Mathematics categories.
This book provides a pedagogical examination of the way in which stochastic models are encountered in applied sciences and techniques such as physics, engineering, biology and genetics, economics and social sciences. It covers Markov and semi-Markov models, as well as their particular cases: Poisson, renewal processes, branching processes, Ehrenfest models, genetic models, optimal stopping, reliability, reservoir theory, storage models, and queuing systems. Given this comprehensive treatment of the subject, students and researchers in applied sciences, as well as anyone looking for an introduction to stochastic models, will find this title of invaluable use.
An Introduction To Stochastic Modeling
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Author : Howard M. Taylor
language : en
Publisher:
Release Date :
An Introduction To Stochastic Modeling written by Howard M. Taylor and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with Stochastic processes categories.
Stochastic Modeling
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Author : Nicolas Lanchier
language : en
Publisher: Springer
Release Date : 2017-01-27
Stochastic Modeling written by Nicolas Lanchier and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-27 with Mathematics categories.
Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the gambler’s ruin chain, branching processes, symmetric random walks, and queueing systems. The third, more research-oriented part of the text, discusses special stochastic processes of interest in physics, biology, and sociology. Additional emphasis is placed on minimal models that have been used historically to develop new mathematical techniques in the field of stochastic processes: the logistic growth process, the Wright –Fisher model, Kingman’s coalescent, percolation models, the contact process, and the voter model. Further treatment of the material explains how these special processes are connected to each other from a modeling perspective as well as their simulation capabilities in C and MatlabTM.
Introduction To Modeling And Analysis Of Stochastic Systems
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Author : V. G. Kulkarni
language : en
Publisher: Springer
Release Date : 2010-11-03
Introduction To Modeling And Analysis Of Stochastic Systems written by V. G. Kulkarni and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-03 with Mathematics categories.
This book provides a self-contained review of all the relevant topics in probability theory. A software package called MAXIM, which runs on MATLAB, is made available for downloading. Vidyadhar G. Kulkarni is Professor of Operations Research at the University of North Carolina at Chapel Hill.
Solutions To Problems In An Introduction To Stochastic Modeling
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Author : Howard M. Taylor
language : en
Publisher:
Release Date : 1998
Solutions To Problems In An Introduction To Stochastic Modeling written by Howard M. Taylor and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
A First Course In Stochastic Models
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Author : Henk C. Tijms
language : en
Publisher: John Wiley & Sons
Release Date : 2003-04-18
A First Course In Stochastic Models written by Henk C. Tijms and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-04-18 with Mathematics categories.
The field of applied probability has changed profoundly in the past twenty years. The development of computational methods has greatly contributed to a better understanding of the theory. A First Course in Stochastic Models provides a self-contained introduction to the theory and applications of stochastic models. Emphasis is placed on establishing the theoretical foundations of the subject, thereby providing a framework in which the applications can be understood. Without this solid basis in theory no applications can be solved. Provides an introduction to the use of stochastic models through an integrated presentation of theory, algorithms and applications. Incorporates recent developments in computational probability. Includes a wide range of examples that illustrate the models and make the methods of solution clear. Features an abundance of motivating exercises that help the student learn how to apply the theory. Accessible to anyone with a basic knowledge of probability. A First Course in Stochastic Models is suitable for senior undergraduate and graduate students from computer science, engineering, statistics, operations resear ch, and any other discipline where stochastic modelling takes place. It stands out amongst other textbooks on the subject because of its integrated presentation of theory, algorithms and applications.