Stochastic Simulation And Monte Carlo Methods

Stochastic Simulation And Monte Carlo Methods Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Stochastic Simulation And Monte Carlo Methods book. This book definitely worth reading, it is an incredibly well-written.

Stochastic Simulation and Monte Carlo Methods

Carl Graham,Denis Talay
Stochastic Simulation and Monte Carlo Methods Book PDF

Author : Carl Graham,Denis Talay
Publisher : Springer Science & Business Media
Page : 260 pages
File Size : 42,8 Mb
Release : 2013-07-16
Category : Mathematics
ISBN : 9783642393631

Get Book

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.

Monte-Carlo Methods and Stochastic Processes

Emmanuel Gobet
Monte Carlo Methods and Stochastic Processes Book PDF

Author : Emmanuel Gobet
Publisher : CRC Press
Page : 216 pages
File Size : 55,7 Mb
Release : 2016-09-15
Category : Mathematics
ISBN : 9781498746250

Get Book

Monte-Carlo Methods and Stochastic Processes by Emmanuel Gobet Pdf

Developed from the author’s course at the Ecole Polytechnique, Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear and nonlinear problems in biology, finance, geophysics, mechanics, chemistry, and other application areas. The text also thoroughly develops the problem of numerical integration and computation of expectation by the Monte-Carlo method. The book begins with a history of Monte-Carlo methods and an overview of three typical Monte-Carlo problems: numerical integration and computation of expectation, simulation of complex distributions, and stochastic optimization. The remainder of the text is organized in three parts of progressive difficulty. The first part presents basic tools for stochastic simulation and analysis of algorithm convergence. The second part describes Monte-Carlo methods for the simulation of stochastic differential equations. The final part discusses the simulation of non-linear dynamics.

Monte Carlo Methods in Financial Engineering

Paul Glasserman
Monte Carlo Methods in Financial Engineering Book PDF

Author : Paul Glasserman
Publisher : Springer Science & Business Media
Page : 603 pages
File Size : 48,7 Mb
Release : 2013-03-09
Category : Mathematics
ISBN : 9780387216171

Get Book

Monte Carlo Methods in Financial Engineering by Paul Glasserman Pdf

From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis

Stochastic Simulation: Algorithms and Analysis

Søren Asmussen,Peter W. Glynn
Stochastic Simulation Algorithms and Analysis Book PDF

Author : Søren Asmussen,Peter W. Glynn
Publisher : Springer Science & Business Media
Page : 476 pages
File Size : 48,7 Mb
Release : 2007-07-14
Category : Mathematics
ISBN : 9780387690339

Get Book

Stochastic Simulation: Algorithms and Analysis by Søren Asmussen,Peter W. Glynn Pdf

Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focuses on general methods; the second half discusses model-specific algorithms. Exercises and illustrations are included.

Handbook of Monte Carlo Methods

Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev
Handbook of Monte Carlo Methods Book PDF

Author : Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev
Publisher : John Wiley & Sons
Page : 772 pages
File Size : 52,6 Mb
Release : 2013-06-06
Category : Mathematics
ISBN : 1118014952

Get Book

Handbook of Monte Carlo Methods by Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev Pdf

A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications More and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the Monte Carlo approach. Handbook of Monte Carlo Methods provides the theory, algorithms, and applications that helps provide a thorough understanding of the emerging dynamics of this rapidly-growing field. The authors begin with a discussion of fundamentals such as how to generate random numbers on a computer. Subsequent chapters discuss key Monte Carlo topics and methods, including: Random variable and stochastic process generation Markov chain Monte Carlo, featuring key algorithms such as the Metropolis-Hastings method, the Gibbs sampler, and hit-and-run Discrete-event simulation Techniques for the statistical analysis of simulation data including the delta method, steady-state estimation, and kernel density estimation Variance reduction, including importance sampling, latin hypercube sampling, and conditional Monte Carlo Estimation of derivatives and sensitivity analysis Advanced topics including cross-entropy, rare events, kernel density estimation, quasi Monte Carlo, particle systems, and randomized optimization The presented theoretical concepts are illustrated with worked examples that use MATLAB®, a related Web site houses the MATLAB® code, allowing readers to work hands-on with the material and also features the author's own lecture notes on Monte Carlo methods. Detailed appendices provide background material on probability theory, stochastic processes, and mathematical statistics as well as the key optimization concepts and techniques that are relevant to Monte Carlo simulation. Handbook of Monte Carlo Methods is an excellent reference for applied statisticians and practitioners working in the fields of engineering and finance who use or would like to learn how to use Monte Carlo in their research. It is also a suitable supplement for courses on Monte Carlo methods and computational statistics at the upper-undergraduate and graduate levels.

Simulation and the Monte Carlo Method

Reuven Y. Rubinstein,Dirk P. Kroese
Simulation and the Monte Carlo Method Book PDF

Author : Reuven Y. Rubinstein,Dirk P. Kroese
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 47,5 Mb
Release : 2016-11-07
Category : Mathematics
ISBN : 9781118632161

Get Book

Simulation and the Monte Carlo Method by Reuven Y. Rubinstein,Dirk P. Kroese Pdf

This accessible new edition explores the major topics in Monte Carlo simulation that have arisen over the past 30 years and presents a sound foundation for problem solving Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the state-of-the-art theory, methods and applications that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as importance (re-)sampling, and the transform likelihood ratio method, the score function method for sensitivity analysis, the stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization, the cross-entropy method for rare events estimation and combinatorial optimization, and application of Monte Carlo techniques for counting problems. An extensive range of exercises is provided at the end of each chapter, as well as a generous sampling of applied examples. The Third Edition features a new chapter on the highly versatile splitting method, with applications to rare-event estimation, counting, sampling, and optimization. A second new chapter introduces the stochastic enumeration method, which is a new fast sequential Monte Carlo method for tree search. In addition, the Third Edition features new material on: • Random number generation, including multiple-recursive generators and the Mersenne Twister • Simulation of Gaussian processes, Brownian motion, and diffusion processes • Multilevel Monte Carlo method • New enhancements of the cross-entropy (CE) method, including the “improved” CE method, which uses sampling from the zero-variance distribution to find the optimal importance sampling parameters • Over 100 algorithms in modern pseudo code with flow control • Over 25 new exercises Simulation and the Monte Carlo Method, Third Edition is an excellent text for upper-undergraduate and beginning graduate courses in stochastic simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method. Reuven Y. Rubinstein, DSc, was Professor Emeritus in the Faculty of Industrial Engineering and Management at Technion-Israel Institute of Technology. He served as a consultant at numerous large-scale organizations, such as IBM, Motorola, and NEC. The author of over 100 articles and six books, Dr. Rubinstein was also the inventor of the popular score-function method in simulation analysis and generic cross-entropy methods for combinatorial optimization and counting. Dirk P. Kroese, PhD, is a Professor of Mathematics and Statistics in the School of Mathematics and Physics of The University of Queensland, Australia. He has published over 100 articles and four books in a wide range of areas in applied probability and statistics, including Monte Carlo methods, cross-entropy, randomized algorithms, tele-traffic c theory, reliability, computational statistics, applied probability, and stochastic modeling.

Markov Chain Monte Carlo

Dani Gamerman,Hedibert F. Lopes
Markov Chain Monte Carlo Book PDF

Author : Dani Gamerman,Hedibert F. Lopes
Publisher : CRC Press
Page : 352 pages
File Size : 52,8 Mb
Release : 2006-05-10
Category : Mathematics
ISBN : 1584885874

Get Book

Markov Chain Monte Carlo by Dani Gamerman,Hedibert F. Lopes Pdf

While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds. Incorporating changes in theory and highlighting new applications, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition presents a concise, accessible, and comprehensive introduction to the methods of this valuable simulation technique. The second edition includes access to an internet site that provides the code, written in R and WinBUGS, used in many of the previously existing and new examples and exercises. More importantly, the self-explanatory nature of the codes will enable modification of the inputs to the codes and variation on many directions will be available for further exploration. Major changes from the previous edition: · More examples with discussion of computational details in chapters on Gibbs sampling and Metropolis-Hastings algorithms · Recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection · Discussion of computation using both R and WinBUGS · Additional exercises and selected solutions within the text, with all data sets and software available for download from the Web · Sections on spatial models and model adequacy The self-contained text units make MCMC accessible to scientists in other disciplines as well as statisticians. The book will appeal to everyone working with MCMC techniques, especially research and graduate statisticians and biostatisticians, and scientists handling data and formulating models. The book has been substantially reinforced as a first reading of material on MCMC and, consequently, as a textbook for modern Bayesian computation and Bayesian inference courses.

Stochastic Simulation and Applications in Finance with MATLAB Programs

Huu Tue Huynh,Van Son Lai,Issouf Soumare
Stochastic Simulation and Applications in Finance with MATLAB Programs Book PDF

Author : Huu Tue Huynh,Van Son Lai,Issouf Soumare
Publisher : John Wiley & Sons
Page : 354 pages
File Size : 45,8 Mb
Release : 2011-11-21
Category : Business & Economics
ISBN : 9780470722138

Get Book

Stochastic Simulation and Applications in Finance with MATLAB Programs by Huu Tue Huynh,Van Son Lai,Issouf Soumare Pdf

Stochastic Simulation and Applications in Finance with MATLAB Programs explains the fundamentals of Monte Carlo simulation techniques, their use in the numerical resolution of stochastic differential equations and their current applications in finance. Building on an integrated approach, it provides a pedagogical treatment of the need-to-know materials in risk management and financial engineering. The book takes readers through the basic concepts, covering the most recent research and problems in the area, including: the quadratic re-sampling technique, the Least Squared Method, the dynamic programming and Stratified State Aggregation technique to price American options, the extreme value simulation technique to price exotic options and the retrieval of volatility method to estimate Greeks. The authors also present modern term structure of interest rate models and pricing swaptions with the BGM market model, and give a full explanation of corporate securities valuation and credit risk based on the structural approach of Merton. Case studies on financial guarantees illustrate how to implement the simulation techniques in pricing and hedging. NOTE TO READER: The CD has been converted to URL. Go to the following website www.wiley.com/go/huyhnstochastic which provides MATLAB programs for the practical examples and case studies, which will give the reader confidence in using and adapting specific ways to solve problems involving stochastic processes in finance.

Rare Event Simulation using Monte Carlo Methods

Gerardo Rubino,Bruno Tuffin
Rare Event Simulation using Monte Carlo Methods Book PDF

Author : Gerardo Rubino,Bruno Tuffin
Publisher : John Wiley & Sons
Page : 278 pages
File Size : 52,7 Mb
Release : 2009-03-18
Category : Mathematics
ISBN : 047074541X

Get Book

Rare Event Simulation using Monte Carlo Methods by Gerardo Rubino,Bruno Tuffin Pdf

In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. Graduate students, researchers and practitioners who wish to learn and apply rare event simulation techniques will find this book beneficial.

Simulation and the Monte Carlo Method

Reuven Y. Rubinstein
Simulation and the Monte Carlo Method Book PDF

Author : Reuven Y. Rubinstein
Publisher : John Wiley & Sons
Page : 304 pages
File Size : 49,8 Mb
Release : 2009-09-25
Category : Mathematics
ISBN : 9780470317228

Get Book

Simulation and the Monte Carlo Method by Reuven Y. Rubinstein Pdf

This book provides the first simultaneous coverage of the statistical aspects of simulation and Monte Carlo methods, their commonalities and their differences for the solution of a wide spectrum of engineering and scientific problems. It contains standard material usually considered in Monte Carlo simulation as well as new material such as variance reduction techniques, regenerative simulation, and Monte Carlo optimization.

Stochastic Simulation

Brian D. Ripley
Stochastic Simulation Book PDF

Author : Brian D. Ripley
Publisher : John Wiley & Sons
Page : 258 pages
File Size : 50,8 Mb
Release : 2009-09-25
Category : Mathematics
ISBN : 9780470317389

Get Book

Stochastic Simulation by Brian D. Ripley Pdf

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. ". . .this is a very competently written and useful addition to the statistical literature; a book every statistician should look at and that many should study!" —Short Book Reviews, International Statistical Institute ". . .reading this book was an enjoyable learning experience. The suggestions and recommendations on the methods [make] this book an excellent reference for anyone interested in simulation. With its compact structure and good coverage of material, it [is] an excellent textbook for a simulation course." —Technometrics ". . .this work is an excellent comprehensive guide to simulation methods, written by a very competent author. It is especially recommended for those users of simulation methods who want more than a 'cook book'. " —Mathematics Abstracts This book is a comprehensive guide to simulation methods with explicit recommendations of methods and algorithms. It covers both the technical aspects of the subject, such as the generation of random numbers, non-uniform random variates and stochastic processes, and the use of simulation. Supported by the relevant mathematical theory, the text contains a great deal of unpublished research material, including coverage of the analysis of shift-register generators, sensitivity analysis of normal variate generators, analysis of simulation output, and more.

Stochastic Simulations in Physics

P.K. MacKeown
Stochastic Simulations in Physics Book PDF

Author : P.K. MacKeown
Publisher : Springer
Page : 486 pages
File Size : 42,8 Mb
Release : 1997-10
Category : Mathematics
ISBN : UOM:39015050453482

Get Book

Stochastic Simulations in Physics by P.K. MacKeown Pdf

The result of 15 years of teaching a final year undergraduate course on computational physics, this book summarises in one neat volume the latest developments of the stochastic phenomena in the context of physics. The approach adopted is a less conventional one, in that there is no canon to be followed in the field. Instead, the topics are chosen so as to give a feeling for the breadth of applications of Monte Carlo methods in physics. An essential reference for students wishing to gain a more technical interest in the subject as a way of getting quantitative answers to a problem. The level of knowledge assumed corresponds to a that of final year undergraduates, but postgraduate students in a number of disciplines will also find the material of value. Contains substantial references to research literature.

Sequential Monte Carlo Methods in Practice

Arnaud Doucet,Nando de Freitas,Neil Gordon
Sequential Monte Carlo Methods in Practice Book PDF

Author : Arnaud Doucet,Nando de Freitas,Neil Gordon
Publisher : Springer Science & Business Media
Page : 590 pages
File Size : 42,6 Mb
Release : 2013-03-09
Category : Mathematics
ISBN : 9781475734379

Get Book

Sequential Monte Carlo Methods in Practice by Arnaud Doucet,Nando de Freitas,Neil Gordon Pdf

Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques.

Spectral Models of Random Fields in Monte Carlo Methods

Serge M. Prigarin
Spectral Models of Random Fields in Monte Carlo Methods Book PDF

Author : Serge M. Prigarin
Publisher : VSP
Page : 220 pages
File Size : 52,7 Mb
Release : 2001
Category : Science
ISBN : 9067643432

Get Book

Spectral Models of Random Fields in Monte Carlo Methods by Serge M. Prigarin Pdf

Spectral models were developed in the 1970s and have appeared to be very promising for various applications. Nowadays, spectral models are extensively used for stochastic simulation in atmosphere and ocean optics, turbulence theory, analysis of pollution transport for porous media, astrophysics, and other fields of science. The spectral models presented in this monograph represent a new class of numerical methods aimed at simulation of random processes and fields. The book is divided into four chapters, which deal with scalar spectral models and some of their applications, vector-valued spectral models, convergence of spectral models, and problems of optimisation and convergence for functional Monte Carlo methods. Furthermore, the monograph includes four appendices, in which auxiliary information is presented and additional problems are discussed. The book will be of value and interest to experts in Monte Carlo methods, as well as to those interested in the theory and applications of stochastic simulation.

Monte-Carlo Methods and Stochastic Processes

Emmanuel Gobet
Monte Carlo Methods and Stochastic Processes Book PDF

Author : Emmanuel Gobet
Publisher : CRC Press
Page : 310 pages
File Size : 55,9 Mb
Release : 2016-09-15
Category : Mathematics
ISBN : 9781498746236

Get Book

Monte-Carlo Methods and Stochastic Processes by Emmanuel Gobet Pdf

Developed from the author’s course at the Ecole Polytechnique, Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear and nonlinear problems in biology, finance, geophysics, mechanics, chemistry, and other application areas. The text also thoroughly develops the problem of numerical integration and computation of expectation by the Monte-Carlo method. The book begins with a history of Monte-Carlo methods and an overview of three typical Monte-Carlo problems: numerical integration and computation of expectation, simulation of complex distributions, and stochastic optimization. The remainder of the text is organized in three parts of progressive difficulty. The first part presents basic tools for stochastic simulation and analysis of algorithm convergence. The second part describes Monte-Carlo methods for the simulation of stochastic differential equations. The final part discusses the simulation of non-linear dynamics.