Stochastic Processes Modeling And Simulation

Author : D N Shanbhag,Calyampudi Radhakrishna Rao
Publisher : Gulf Professional Publishing
Page : 1028 pages
File Size : 49,7 Mb
Release : 2003-02-24
Category : Mathematics
ISBN : 0444500138

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Stochastic Processes: Modeling and Simulation by D N Shanbhag,Calyampudi Radhakrishna Rao Pdf

This sequel to volume 19 of Handbook on Statistics on Stochastic Processes: Modelling and Simulation is concerned mainly with the theme of reviewing and, in some cases, unifying with new ideas the different lines of research and developments in stochastic processes of applied flavour. This volume consists of 23 chapters addressing various topics in stochastic processes. These include, among others, those on manufacturing systems, random graphs, reliability, epidemic modelling, self-similar processes, empirical processes, time series models, extreme value therapy, applications of Markov chains, modelling with Monte Carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The scope of the project involving this volume as well as volume 19 is already clarified in the preface of volume 19. The present volume completes the aim of the project and should serve as an aid to students, teachers, researchers and practitioners interested in applied stochastic processes.

Author : Barry L. Nelson
Publisher : Courier Corporation
Page : 338 pages
File Size : 52,6 Mb
Release : 2012-10-11
Category : Mathematics
ISBN : 9780486139944

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Stochastic Modeling by Barry L. Nelson Pdf

Coherent introduction to techniques also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Includes formulation of models, analysis, and interpretation of results. 1995 edition.

Author : D. N. Shanbhag,Calyampudi Radhakrishna Rao
Publisher : Unknown
Page : 128 pages
File Size : 46,6 Mb
Release : 2009
Category : Electronic
ISBN : OCLC:804515085

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Stochastic Processes by D. N. Shanbhag,Calyampudi Radhakrishna Rao Pdf

Author : Nicolas Lanchier
Publisher : Springer
Page : 303 pages
File Size : 53,6 Mb
Release : 2017-01-27
Category : Mathematics
ISBN : 9783319500386

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Stochastic Modeling by Nicolas Lanchier Pdf

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.

Author : Yuriy V. Kozachenko,Oleksandr O. Pogorilyak,Iryna V. Rozora,Antonina M. Tegza
Publisher : Elsevier
Page : 346 pages
File Size : 51,6 Mb
Release : 2016-11-22
Category : Mathematics
ISBN : 9780081020852

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Simulation of Stochastic Processes with Given Accuracy and Reliability by Yuriy V. Kozachenko,Oleksandr O. Pogorilyak,Iryna V. Rozora,Antonina M. Tegza Pdf

Simulation has now become an integral part of research and development across many fields of study. Despite the large amounts of literature in the field of simulation and modeling, one recurring problem is the issue of accuracy and confidence level of constructed models. By outlining the new approaches and modern methods of simulation of stochastic processes, this book provides methods and tools in measuring accuracy and reliability in functional spaces. The authors explore analysis of the theory of Sub-Gaussian (including Gaussian one) and Square Gaussian random variables and processes and Cox processes. Methods of simulation of stochastic processes and fields with given accuracy and reliability in some Banach spaces are also considered. Provides an analysis of the theory of Sub-Gaussian (including Gaussian one) and Square Gaussian random variables and processes Contains information on the study of the issue of accuracy and confidence level of constructed models not found in other books on the topic Provides methods and tools in measuring accuracy and reliability in functional spaces

Author : Roe Goodman
Publisher : Courier Corporation
Page : 370 pages
File Size : 41,5 Mb
Release : 2006-01-01
Category : Mathematics
ISBN : 9780486450377

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Introduction to Stochastic Models by Roe Goodman Pdf

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.

Author : Stefano M. Iacus,Nakahiro Yoshida
Publisher : Springer
Page : 268 pages
File Size : 46,7 Mb
Release : 2018-06-01
Category : Computers
ISBN : 9783319555690

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Simulation and Inference for Stochastic Processes with YUIMA by Stefano M. Iacus,Nakahiro Yoshida Pdf

The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes. The package performs various central statistical analyses such as quasi maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on. YUIMA also supports stochastic numerical analysis by fast computation of the expected value of functionals of stochastic processes through automatic asymptotic expansion by means of the Malliavin calculus. All models can be multidimensional, multiparametric or non parametric.The book explains briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation experiments and applications to real data. Although these processes have been originally proposed in physics and more recently in finance, they are becoming popular also in biology due to the fact the time course experimental data are now available. The YUIMA package, available on CRAN, can be freely downloaded and this companion book will make the user able to start his or her analysis from the first page.

Author : Georg Ch. Pflug
Publisher : Springer Science & Business Media
Page : 384 pages
File Size : 45,8 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9781461314493

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Optimization of Stochastic Models by Georg Ch. Pflug Pdf

Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. The field is quite new and yet the number of publications is enormous. This book does not even try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. Optimization of Stochastic Models: The Interface Between Simulation and Optimization is suitable as a text for a graduate level course on Stochastic Models or as a secondary text for a graduate level course in Operations Research.

Author : Fred Espen Benth,Jurate Saltyte Benth
Publisher : Unknown
Page : 298 pages
File Size : 52,9 Mb
Release : 2018-04
Category : Electronic
ISBN : 1788023463

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Stochastic Processes by Fred Espen Benth,Jurate Saltyte Benth Pdf

Author : Vincenzo Capasso,David Bakstein
Publisher : Springer Science & Business Media
Page : 348 pages
File Size : 47,9 Mb
Release : 2008-01-03
Category : Mathematics
ISBN : 9780817644284

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An Introduction to Continuous-Time Stochastic Processes by Vincenzo Capasso,David Bakstein Pdf

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.

Author : Carl Graham,Denis Talay
Publisher : Springer Science & Business Media
Page : 264 pages
File Size : 50,6 Mb
Release : 2013-07-16
Category : Mathematics
ISBN : 9783642393631

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Stochastic Simulation and Monte Carlo Methods by Carl Graham,Denis Talay Pdf

In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners’ aim to simulate more and more complex systems, and thus use random parameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Itô integrals and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view. The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations, who will benefit from the ability to reliably estimate and control the accuracy of their simulations.

Author : Barry L. Nelson,Linda Pei
Publisher : Springer Nature
Page : 323 pages
File Size : 52,6 Mb
Release : 2021-11-10
Category : Business & Economics
ISBN : 9783030861940

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Foundations and Methods of Stochastic Simulation by Barry L. Nelson,Linda Pei Pdf

This graduate-level textbook covers modelling, programming and analysis of stochastic computer simulation experiments, including the mathematical and statistical foundations of simulation and why it works. The book is rigorous and complete, but concise and accessible, providing all necessary background material. Object-oriented programming of simulations is illustrated in Python, while the majority of the book is programming language independent. In addition to covering the foundations of simulation and simulation programming for applications, the text prepares readers to use simulation in their research. A solutions manual for end-of-chapter exercises is available for instructors.

Author : Gerald S. Shedler
Publisher : Academic Press
Page : 424 pages
File Size : 43,6 Mb
Release : 1993
Category : Education
ISBN : UOM:39015028464652

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Regenerative Stochastic Simulation by Gerald S. Shedler Pdf

Discrete-event simulations. Regenerative stochastic processes. Regenerative simulation. Networks of queues. Passage times. Simulations with simultaneous events. Limit theorems for stochastic processes. Random number generation.

Author : Peter J. Haas
Publisher : Springer Science & Business Media
Page : 523 pages
File Size : 47,9 Mb
Release : 2006-04-10
Category : Mathematics
ISBN : 9780387215525

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Stochastic Petri Nets by Peter J. Haas Pdf

Written by a leading researcher this book presents an introduction to Stochastic Petri Nets covering the modeling power of the proposed SPN model, the stability conditions and the simulation methods. Its unique and well-written approach provides a timely and important addition to the literature. Appeals to a wide range of researchers in engineering, computer science, mathematics and OR.

Author : Howard M. Taylor,Samuel Karlin
Publisher : Academic Press
Page : 410 pages
File Size : 41,6 Mb
Release : 2014-05-10
Category : Mathematics
ISBN : 9781483269276

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An Introduction to Stochastic Modeling by Howard M. Taylor,Samuel Karlin Pdf

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.