An Introduction To Stochastic Modeling

An Introduction to Stochastic Modeling PDF
Author: Howard M. Taylor
Publisher: Academic Press
ISBN: 1483269272
Size: 38.86 MB
Format: PDF, ePub
Category : Mathematics
Languages : en
Pages : 410
View: 1990

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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.

Introduction To Stochastic Models

Introduction to Stochastic Models PDF
Author: Roe Goodman
Publisher: Courier Corporation
ISBN: 0486450376
Size: 34.44 MB
Format: PDF, ePub, Mobi
Category : Mathematics
Languages : en
Pages : 355
View: 7579

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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.

Introduction To Stochastic Models

Introduction to Stochastic Models PDF
Author: Marius Iosifescu
Publisher: John Wiley & Sons
ISBN: 1118623525
Size: 36.81 MB
Format: PDF, ePub, Docs
Category : Mathematics
Languages : en
Pages : 320
View: 5360

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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

An Introduction to Stochastic Modeling PDF
Author: Mark Pinsky
Publisher: Academic Press
ISBN: 0123814162
Size: 62.98 MB
Format: PDF
Category : Mathematics
Languages : en
Pages : 563
View: 1843

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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 Matrix Analytic Methods In Stochastic Modeling

Introduction to Matrix Analytic Methods in Stochastic Modeling PDF
Author: G. Latouche
Publisher: SIAM
ISBN: 0898714257
Size: 44.24 MB
Format: PDF, Docs
Category : Mathematics
Languages : en
Pages : 334
View: 858

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Presents the basic mathematical ideas and algorithms of the matrix analytic theory in a readable, up-to-date, and comprehensive manner.

Stochastic Models Analysis And Applications

Stochastic Models  Analysis and Applications PDF
Author: B. R. Bhat
Publisher: New Age International
ISBN: 9788122412284
Size: 37.78 MB
Format: PDF, Mobi
Category : Mathematical statistics
Languages : en
Pages : 408
View: 4561

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The Book Presents A Systematic Exposition Of The Basic Theory And Applications Of Stochastic Models.Emphasising The Modelling Rather Than Mathematical Aspects Of Stochastic Processes, The Book Bridges The Gap Between The Theory And Applications Of These Processes.The Basic Building Blocks Of Model Construction Are Explained In A Step By Step Manner, Starting From The Simplest Model Of Random Walk And Proceeding Gradually To More Complicated Models. Several Examples Are Given Throughout The Text To Illustrate Important Analytical Properties As Well As To Provide Applications.The Book Also Includes A Detailed Chapter On Inference For Stochastic Processes. This Chapter Highlights Some Of The Recent Developments In The Subject And Explains Them Through Illustrative Examples.An Important Feature Of The Book Is The Complements And Problems Section At The End Of Each Chapter Which Presents (I) Additional Properties Of The Model, (Ii) Extensions Of The Model, And (Iii) Applications Of The Model To Different Areas.With All These Features, This Is An Invaluable Text For Post-Graduate Students Of Statistics, Mathematics And Operation Research.

Introduction To Stochastic Calculus With Applications

Introduction to Stochastic Calculus with Applications PDF
Author: Fima C. Klebaner
Publisher: Imperial College Press
ISBN: 1860945554
Size: 39.85 MB
Format: PDF, ePub, Mobi
Category : Mathematics
Languages : en
Pages : 416
View: 4591

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This book presents a concise treatment of stochastic calculus and its applications. It gives a simple but rigorous treatment of the subject including a range of advanced topics, it is useful for practitioners who use advanced theoretical results. It covers advanced applications, such as models in mathematical finance, biology and engineering.Self-contained and unified in presentation, the book contains many solved examples and exercises. It may be used as a textbook by advanced undergraduates and graduate students in stochastic calculus and financial mathematics. It is also suitable for practitioners who wish to gain an understanding or working knowledge of the subject. For mathematicians, this book could be a first text on stochastic calculus; it is good companion to more advanced texts by a way of examples and exercises. For people from other fields, it provides a way to gain a working knowledge of stochastic calculus. It shows all readers the applications of stochastic calculus methods and takes readers to the technical level required in research and sophisticated modelling.This second edition contains a new chapter on bonds, interest rates and their options. New materials include more worked out examples in all chapters, best estimators, more results on change of time, change of measure, random measures, new results on exotic options, FX options, stochastic and implied volatility, models of the age-dependent branching process and the stochastic Lotka-Volterra model in biology, non-linear filtering in engineering and five new figures.Instructors can obtain slides of the text from the author.

An Elementary Introduction To Stochastic Interest Rate Modeling

An Elementary Introduction to Stochastic Interest Rate Modeling PDF
Author: Nicolas Privault
Publisher: World Scientific
ISBN: 9814390852
Size: 78.22 MB
Format: PDF
Category : Business & Economics
Languages : en
Pages : 228
View: 6501

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Interest rate modeling and the pricing of related derivatives remain subjects of increasing importance in financial mathematics and risk management. This book provides an accessible introduction to these topics by a step-by-step presentation of concepts with a focus on explicit calculations. Each chapter is accompanied with exercises and their complete solutions, making the book suitable for advanced undergraduate and graduate level students. This second edition retains the main features of the first edition while incorporating a complete revision of the text as well as additional exercises with their solutions, and a new introductory chapter on credit risk. The stochastic interest rate models considered range from standard short rate to forward rate models, with a treatment of the pricing of related derivatives such as caps and swaptions under forward measures. Some more advanced topics including the BGM model and an approach to its calibration are also covered.

Mathematical Epidemiology

Mathematical Epidemiology PDF
Author: Fred Brauer
Publisher: Springer Science & Business Media
ISBN: 3540789103
Size: 61.45 MB
Format: PDF, ePub, Docs
Category : Medical
Languages : en
Pages : 414
View: 1292

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Based on lecture notes of two summer schools with a mixed audience from mathematical sciences, epidemiology and public health, this volume offers a comprehensive introduction to basic ideas and techniques in modeling infectious diseases, for the comparison of strategies to plan for an anticipated epidemic or pandemic, and to deal with a disease outbreak in real time. It covers detailed case studies for diseases including pandemic influenza, West Nile virus, and childhood diseases. Models for other diseases including Severe Acute Respiratory Syndrome, fox rabies, and sexually transmitted infections are included as applications. Its chapters are coherent and complementary independent units. In order to accustom students to look at the current literature and to experience different perspectives, no attempt has been made to achieve united writing style or unified notation. Notes on some mathematical background (calculus, matrix algebra, differential equations, and probability) have been prepared and may be downloaded at the web site of the Centre for Disease Modeling (www.cdm.yorku.ca).

Introduction To Modeling And Analysis Of Stochastic Systems

Introduction to Modeling and Analysis of Stochastic Systems PDF
Author: V. G. Kulkarni
Publisher: Springer
ISBN: 9781441917720
Size: 33.13 MB
Format: PDF, Docs
Category : Mathematics
Languages : en
Pages : 313
View: 5644

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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.

Introduction To Stochastic Search And Optimization

Introduction to Stochastic Search and Optimization PDF
Author: James C. Spall
Publisher: John Wiley & Sons
ISBN: 0471441902
Size: 79.25 MB
Format: PDF, Docs
Category : Mathematics
Languages : en
Pages : 618
View: 3684

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A unique interdisciplinary foundation for real-world problemsolving Stochastic search and optimization techniques are used in a vastnumber of areas, including aerospace, medicine, transportation, andfinance, to name but a few. Whether the goal is refining the designof a missile or aircraft, determining the effectiveness of a newdrug, developing the most efficient timing strategies for trafficsignals, or making investment decisions in order to increaseprofits, stochastic algorithms can help researchers andpractitioners devise optimal solutions to countless real-worldproblems. Introduction to Stochastic Search and Optimization: Estimation,Simulation, and Control is a graduate-level introduction to theprinciples, algorithms, and practical aspects of stochasticoptimization, including applications drawn from engineering,statistics, and computer science. The treatment is both rigorousand broadly accessible, distinguishing this text from much of thecurrent literature and providing students, researchers, andpractitioners with a strong foundation for the often-daunting taskof solving real-world problems. The text covers a broad range of today’s most widely usedstochastic algorithms, including: Random search Recursive linear estimation Stochastic approximation Simulated annealing Genetic and evolutionary methods Machine (reinforcement) learning Model selection Simulation-based optimization Markov chain Monte Carlo Optimal experimental design The book includes over 130 examples, Web links to software anddata sets, more than 250 exercises for the reader, and an extensivelist of references. These features help make the text an invaluableresource for those interested in the theory or practice ofstochastic search and optimization.

An Introduction To Continuous Time Stochastic Processes

An Introduction to Continuous Time Stochastic Processes PDF
Author: Vincenzo Capasso
Publisher: Springer Science & Business Media
ISBN: 9780817644284
Size: 42.27 MB
Format: PDF, ePub, Docs
Category : Mathematics
Languages : en
Pages : 344
View: 4294

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This concisely written book is a rigorous and self-contained introduction to the theory of continuous-time stochastic processes. Balancing theory and applications, the authors use stochastic methods and concrete examples to model real-world problems from engineering, biomathematics, biotechnology, and finance. Suitable as a textbook for graduate or advanced undergraduate courses, the work may also be used for self-study or as a reference. The book will be of interest to students, pure and applied mathematicians, and researchers or practitioners in mathematical finance, biomathematics, physics, and engineering.