An Introduction to Stochastic Modeling


Author: Howard M. Taylor,Samuel Karlin
Publisher: Academic Press
ISBN: 1483269272
Category: Mathematics
Page: 410
View: 8907
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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.

An Introduction to Stochastic Modeling


Author: Mark A. Pinsky,Samuel Karlin
Publisher: Academic Press
ISBN: 0123814162
Category: Mathematics
Page: 563
View: 7339
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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, Third 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. * Realistic applications from a variety of disciplines integrated throughout the text * Plentiful, updated and more rigorous problems, including computer "challenges" * Revised end-of-chapter exercises sets-in all, 250 exercises with answers * New chapter on Brownian motion and related processes * Additional sections on Matingales and Poisson process * Solutions manual available to adopting instructors

An Introduction to Stochastic Modeling, Student Solutions Manual (e-only)


Author: Mark Pinsky,Samuel Karlin
Publisher: Academic Press
ISBN: 9780123852267
Category: Mathematics
Page: 510
View: 6325
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An Introduction to Stochastic Modeling, Student Solutions Manual (e-only)

Introduction to Stochastic Models


Author: Marius Iosifescu,Nikolaos Limnios,Gheorghe Oprisan
Publisher: John Wiley & Sons
ISBN: 1118623525
Category: Mathematics
Page: 320
View: 5865
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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.

Elementare Wahrscheinlichkeitstheorie und stochastische Prozesse


Author: Kai L. Chung
Publisher: Springer-Verlag
ISBN: 3642670334
Category: Mathematics
Page: 346
View: 2959
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Aus den Besprechungen: "Unter den zahlreichen Einführungen in die Wahrscheinlichkeitsrechnung bildet dieses Buch eine erfreuliche Ausnahme. Der Stil einer lebendigen Vorlesung ist über Niederschrift und Übersetzung hinweg erhalten geblieben. In jedes Kapitel wird sehr anschaulich eingeführt. Sinn und Nützlichkeit der mathematischen Formulierungen werden den Lesern nahegebracht. Die wichtigsten Zusammenhänge sind als mathematische Sätze klar formuliert." #FREQUENZ#1

An Introduction to Differential Equations

Stochastic Modeling, Methods and Analysis(Volume 2)
Author: Anil G Ladde,G S Ladde
Publisher: World Scientific Publishing Company
ISBN: 9814397393
Category: Mathematics
Page: 636
View: 3647
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Volume 1: Deterministic Modeling, Methods and Analysis For more than half a century, stochastic calculus and stochastic differential equations have played a major role in analyzing the dynamic phenomena in the biological and physical sciences, as well as engineering. The advancement of knowledge in stochastic differential equations is spreading rapidly across the graduate and postgraduate programs in universities around the globe. This will be the first available book that can be used in any undergraduate/graduate stochastic modeling/applied mathematics courses and that can be used by an interdisciplinary researcher with a minimal academic background. An Introduction to Differential Equations: Volume 2 is a stochastic version of Volume 1 (“An Introduction to Differential Equations: Deterministic Modeling, Methods and Analysis”). Both books have a similar design, but naturally, differ by calculi. Again, both volumes use an innovative style in the presentation of the topics, methods and concepts with adequate preparation in deterministic Calculus. Errata Errata (32 KB)

An Introduction to Continuous-Time Stochastic Processes

Theory, Models, and Applications to Finance, Biology, and Medicine
Author: Vincenzo Capasso,David Bakstein
Publisher: Springer Science & Business Media
ISBN: 9780817644284
Category: Mathematics
Page: 344
View: 8211
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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.

An Introduction to Stochastic Dynamics


Author: Jinqiao Duan
Publisher: Cambridge University Press
ISBN: 1107075394
Category: Mathematics
Page: 307
View: 4989
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An accessible introduction for applied mathematicians to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty.

A First Course in Stochastic Models


Author: H. C. Tijms
Publisher: John Wiley & Sons
ISBN: 9780471498803
Category: Mathematics
Page: 478
View: 8765
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The book is intended as a first introduction to stochastic models for students in computer science, engineering, statistics and operations research.

Stochastik

Einführung in die Wahrscheinlichkeitstheorie und Statistik
Author: Hans-Otto Georgii
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110359707
Category: Mathematics
Page: 448
View: 8485
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Due to the extremely positive reception of this textbook, it is now being published in its 5th edition. The book provides an introduction to the key ideas and elements of probability theory and statistics. Stochastic concepts, models, and methods are highlighted through typical application examples, then analyzed theoretically and systematically explored.

An Introduction to Probabilistic Modeling


Author: Pierre Bremaud
Publisher: Springer Science & Business Media
ISBN: 1461210461
Category: Mathematics
Page: 208
View: 2436
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Introduction to the basic concepts of probability theory: independence, expectation, convergence in law and almost-sure convergence. Short expositions of more advanced topics such as Markov Chains, Stochastic Processes, Bayesian Decision Theory and Information Theory.

An Introduction to Mathematical Modeling


Author: Edward A. Bender
Publisher: Courier Corporation
ISBN: 0486137120
Category: Mathematics
Page: 272
View: 7082
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Accessible text features over 100 reality-based examples pulled from the science, engineering, and operations research fields. Prerequisites: ordinary differential equations, continuous probability. Numerous references. Includes 27 black-and-white figures. 1978 edition.

Introduction to Modeling and Analysis of Stochastic Systems


Author: V. G. Kulkarni
Publisher: Springer
ISBN: 9781441917720
Category: Mathematics
Page: 313
View: 9674
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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.

Mathematical Epidemiology


Author: Fred Brauer,Pauline van den Driessche,J. Wu
Publisher: Springer Science & Business Media
ISBN: 3540789103
Category: Medical
Page: 414
View: 8429
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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).

Wahrscheinlichkeitstheorie und Stochastische Prozesse


Author: Michael Mürmann
Publisher: Springer-Verlag
ISBN: 364238160X
Category: Mathematics
Page: 428
View: 9415
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Dieses Lehrbuch beschäftigt sich mit den zentralen Gebieten einer maßtheoretisch orientierten Wahrscheinlichkeitstheorie im Umfang einer zweisemestrigen Vorlesung. Nach den Grundlagen werden Grenzwertsätze und schwache Konvergenz behandelt. Es folgt die Darstellung und Betrachtung der stochastischen Abhängigkeit durch die bedingte Erwartung, die mit der Radon-Nikodym-Ableitung realisiert wird. Sie wird angewandt auf die Theorie der stochastischen Prozesse, die nach der allgemeinen Konstruktion aus der Untersuchung von Martingalen und Markov-Prozessen besteht. Neu in einem Lehrbuch über allgemeine Wahrscheinlichkeitstheorie ist eine Einführung in die stochastische Analysis von Semimartingalen auf der Grundlage einer geeigneten Stetigkeitsbedingung mit Anwendungen auf die Theorie der Finanzmärkte. Das Buch enthält zahlreiche Übungen, teilweise mit Lösungen. Neben der Theorie vertiefen Anmerkungen, besonders zu mathematischen Modellen für Phänomene der Realität, das Verständnis.​

An Introduction to Sparse Stochastic Processes


Author: Michael Unser,Pouya D. Tafti
Publisher: Cambridge University Press
ISBN: 1316061604
Category: Technology & Engineering
Page: N.A
View: 785
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Providing a novel approach to sparsity, this comprehensive book presents the theory of stochastic processes that are ruled by linear stochastic differential equations, and that admit a parsimonious representation in a matched wavelet-like basis. Two key themes are the statistical property of infinite divisibility, which leads to two distinct types of behaviour - Gaussian and sparse - and the structural link between linear stochastic processes and spline functions, which is exploited to simplify the mathematical analysis. The core of the book is devoted to investigating sparse processes, including a complete description of their transform-domain statistics. The final part develops practical signal-processing algorithms that are based on these models, with special emphasis on biomedical image reconstruction. This is an ideal reference for graduate students and researchers with an interest in signal/image processing, compressed sensing, approximation theory, machine learning, or statistics.

Stochastic Models: Analysis and Applications


Author: B. R. Bhat
Publisher: New Age International
ISBN: 9788122412284
Category: Mathematical statistics
Page: 408
View: 4896
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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


Author: Fima C. Klebaner
Publisher: Imperial College Press
ISBN: 1860945554
Category: Mathematics
Page: 416
View: 720
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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.

Introduction to Probability and Stochastic Processes with Applications


Author: Liliana Blanco Castañeda,Viswanathan Arunachalam,Selvamuthu Dharmaraja
Publisher: John Wiley & Sons
ISBN: 1118344960
Category: Mathematics
Page: 614
View: 6866
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An easily accessible, real-world approach to probability andstochastic processes Introduction to Probability and Stochastic Processes withApplications presents a clear, easy-to-understand treatment ofprobability and stochastic processes, providing readers with asolid foundation they can build upon throughout their careers. Withan emphasis on applications in engineering, applied sciences,business and finance, statistics, mathematics, and operationsresearch, the book features numerous real-world examples thatillustrate how random phenomena occur in nature and how to useprobabilistic techniques to accurately model these phenomena. The authors discuss a broad range of topics, from the basicconcepts of probability to advanced topics for further study,including Itô integrals, martingales, and sigma algebras.Additional topical coverage includes: Distributions of discrete and continuous random variablesfrequently used in applications Random vectors, conditional probability, expectation, andmultivariate normal distributions The laws of large numbers, limit theorems, and convergence ofsequences of random variables Stochastic processes and related applications, particularly inqueueing systems Financial mathematics, including pricing methods such asrisk-neutral valuation and the Black-Scholes formula Extensive appendices containing a review of the requisitemathematics and tables of standard distributions for use inapplications are provided, and plentiful exercises, problems, andsolutions are found throughout. Also, a related website featuresadditional exercises with solutions and supplementary material forclassroom use. Introduction to Probability and StochasticProcesses with Applications is an ideal book for probabilitycourses at the upper-undergraduate level. The book is also avaluable reference for researchers and practitioners in the fieldsof engineering, operations research, and computer science whoconduct data analysis to make decisions in their everyday work.