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Elements Of Stochastic Modelling (2nd Edition)

2014-06-30 Mathematics
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Release : 2014-06-30
Genre : Mathematics
Kind : eBook
Book Rating : 180/5 ( reviews)

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Book Synopsis Elements Of Stochastic Modelling (2nd Edition) by : Konstantin Borovkov

Download or read book Elements Of Stochastic Modelling (2nd Edition) written by Konstantin Borovkov. This book was released on 2014-06-30. Available in PDF, EPUB and Kindle. Book excerpt: This is the expanded second edition of a successful textbook that provides a broad introduction to important areas of stochastic modelling. The original text was developed from lecture notes for a one-semester course for third-year science and actuarial students at the University of Melbourne. It reviewed the basics of probability theory and then covered the following topics: Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory, basic renewal theory, elements of time series and simulation.The present edition adds new chapters on elements of stochastic calculus and introductory mathematical finance that logically complement the topics chosen for the first edition. This makes the book suitable for a larger variety of university courses presenting the fundamentals of modern stochastic modelling. Instead of rigorous proofs we often give only sketches of the arguments, with indications as to why a particular result holds and also how it is related to other results, and illustrate them by examples. Wherever possible, the book includes references to more specialised texts on respective topics that contain both proofs and more advanced material.

Elements Of Stochastic Modelling (Third Edition)

2024-02-08 Mathematics
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Release : 2024-02-08
Genre : Mathematics
Kind : eBook
Book Rating : 401/5 ( reviews)

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Book Synopsis Elements Of Stochastic Modelling (Third Edition) by : Konstantin Borovkov

Download or read book Elements Of Stochastic Modelling (Third Edition) written by Konstantin Borovkov. This book was released on 2024-02-08. Available in PDF, EPUB and Kindle. Book excerpt: This is a thoroughly revised and expanded third edition of a successful university textbook that provides a broad introduction to key areas of stochastic modelling. The previous edition was developed from lecture notes for two one-semester courses for third-year science and actuarial students at the University of Melbourne.This book reviews the basics of probability theory and presents topics on Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory, basic renewal theory, elements of time series and simulation. It also features elements of stochastic calculus and introductory mathematical finance. This makes the book suitable for a larger variety of university courses presenting the fundamentals of modern stochastic modelling.To make the text covering a lot of material more appealing and accessible to the reader, instead of rigorous proofs we often give only sketches of the arguments, with indications as to why a particular result holds and also how it is related to other results, and illustrate them by examples. It is in this aspect that the present, third edition differs from the second one: the included background material and argument sketches have been extended, made more graphical and informative. The whole text was reviewed and streamlined wherever possible to make the book more attractive and useful for readers. Where appropriate, the book includes references to more specialised texts on respective topics that contain both complete proofs and more advanced material.

Elements of Stochastic Modelling (Third Edition)

2024 Business & Economics
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Release : 2024
Genre : Business & Economics
Kind : eBook
Book Rating : 380/5 ( reviews)

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Book Synopsis Elements of Stochastic Modelling (Third Edition) by : Konstantin Borovkov

Download or read book Elements of Stochastic Modelling (Third Edition) written by Konstantin Borovkov. This book was released on 2024. Available in PDF, EPUB and Kindle. Book excerpt: This is a thoroughly revised and expanded third edition of a successful university textbook that provides a broad introduction to key areas of stochastic modelling. The original text was developed from lecture notes for a one-semester course for third-year science and actuarial students at the University of Melbourne.This book reviews the basics of probability theory and presents topics on Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory, basic renewal theory, elements of time series and simulation. It also features elements of stochastic calculus and introductory mathematical finance. Thus enhancing the book's suitability for a larger variety of university courses presenting the fundamentals of modern stochastic modelling.To make the text covering a lot of material more appealing and accessible to the reader, instead of rigorous proofs we often give only sketches of the arguments, with indications as to why a particular result holds and also how it is related to other results, and illustrate them by examples. It is in this aspect that the present, third edition differs from the second one: the included background material and argument sketches have been extended, made more graphical and informative. The whole text was reviewed and streamlined wherever possible for it to be more attractive and useful for readers. Wherever possible, the book includes references to more specialised texts on respective topics that contain both proofs and more advanced material.

Introduction to Stochastic Models

2006-01-01 Mathematics
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Release : 2006-01-01
Genre : Mathematics
Kind : eBook
Book Rating : 376/5 ( reviews)

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Book Synopsis Introduction to Stochastic Models by : Roe Goodman

Download or read book Introduction to Stochastic Models written by Roe Goodman. This book was released on 2006-01-01. Available in PDF, EPUB and Kindle. Book excerpt: 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

2014-05-10 Mathematics
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Release : 2014-05-10
Genre : Mathematics
Kind : eBook
Book Rating : 272/5 ( reviews)

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Book Synopsis An Introduction to Stochastic Modeling by : Howard M. Taylor

Download or read book An Introduction to Stochastic Modeling written by Howard M. Taylor. This book was released on 2014-05-10. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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