Essentials Of Monte Carlo Simulation

Author : Nick T. Thomopoulos
Publisher : Springer Science & Business Media
Page : 184 pages
File Size : 49,8 Mb
Release : 2012-12-19
Category : Mathematics
ISBN : 9781461460220

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Essentials of Monte Carlo Simulation by Nick T. Thomopoulos Pdf

Essentials of Monte Carlo Simulation focuses on the fundamentals of Monte Carlo methods using basic computer simulation techniques. The theories presented in this text deal with systems that are too complex to solve analytically. As a result, readers are given a system of interest and constructs using computer code, as well as algorithmic models to emulate how the system works internally. After the models are run several times, in a random sample way, the data for each output variable(s) of interest is analyzed by ordinary statistical methods. This book features 11 comprehensive chapters, and discusses such key topics as random number generators, multivariate random variates, and continuous random variates. Over 100 numerical examples are presented as part of the appendix to illustrate useful real world applications. The text also contains an easy to read presentation with minimal use of difficult mathematical concepts. Very little has been published in the area of computer Monte Carlo simulation methods, and this book will appeal to students and researchers in the fields of Mathematics and Statistics.

Author : Springer
Publisher : Unknown
Page : 192 pages
File Size : 41,8 Mb
Release : 2012-12-01
Category : Electronic
ISBN : 1461460239

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Essentials of Monte Carlo Simulation by Springer Pdf

Author : Paul Glasserman
Publisher : Springer Science & Business Media
Page : 603 pages
File Size : 46,7 Mb
Release : 2013-03-09
Category : Mathematics
ISBN : 9780387216171

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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

Author : Enrico Zio
Publisher : Springer Science & Business Media
Page : 204 pages
File Size : 49,6 Mb
Release : 2012-11-02
Category : Technology & Engineering
ISBN : 9781447145882

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The Monte Carlo Simulation Method for System Reliability and Risk Analysis by Enrico Zio Pdf

Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling. Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques. This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergraduate and graduate students as well as researchers and practitioners. It provides a powerful tool for all those involved in system analysis for reliability, maintenance and risk evaluations.

Author : Don L. McLeish
Publisher : John Wiley & Sons
Page : 308 pages
File Size : 53,8 Mb
Release : 2011-09-13
Category : Business & Economics
ISBN : 9781118160947

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Monte Carlo Simulation and Finance by Don L. McLeish Pdf

Monte Carlo methods have been used for decades in physics, engineering, statistics, and other fields. Monte Carlo Simulation and Finance explains the nuts and bolts of this essential technique used to value derivatives and other securities. Author and educator Don McLeish examines this fundamental process, and discusses important issues, including specialized problems in finance that Monte Carlo and Quasi-Monte Carlo methods can help solve and the different ways Monte Carlo methods can be improved upon. This state-of-the-art book on Monte Carlo simulation methods is ideal for finance professionals and students. Order your copy today.

Author : Kurt Binder,Dieter W. Heermann
Publisher : Springer Science & Business Media
Page : 132 pages
File Size : 53,8 Mb
Release : 2013-11-11
Category : Science
ISBN : 9783662302736

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Monte Carlo Simulation in Statistical Physics by Kurt Binder,Dieter W. Heermann Pdf

When learning very formal material one comes to a stage where one thinks one has understood the material. Confronted with a "realiife" problem, the passivity of this understanding sometimes becomes painfully elear. To be able to solve the problem, ideas, methods, etc. need to be ready at hand. They must be mastered (become active knowledge) in order to employ them successfully. Starting from this idea, the leitmotif, or aim, of this book has been to elose this gap as much as possible. How can this be done? The material presented here was born out of a series of lectures at the Summer School held at Figueira da Foz (Portugal) in 1987. The series of lectures was split into two concurrent parts. In one part the "formal material" was presented. Since the background of those attending varied widely, the presentation of the formal material was kept as pedagogic as possible. In the formal part the general ideas behind the Monte Carlo method were developed. The Monte Carlo method has now found widespread appli cation in many branches of science such as physics, chemistry, and biology. Because of this, the scope of the lectures had to be narrowed down. We could not give a complete account and restricted the treatment to the ap plication of the Monte Carlo method to the physics of phase transitions. Here particular emphasis is placed on finite-size effects.

Author : Christian Robert,George Casella
Publisher : Springer Science & Business Media
Page : 297 pages
File Size : 55,9 Mb
Release : 2010
Category : Computers
ISBN : 9781441915757

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Introducing Monte Carlo Methods with R by Christian Robert,George Casella Pdf

This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.

Author : Paolo Brandimarte
Publisher : John Wiley & Sons
Page : 688 pages
File Size : 43,9 Mb
Release : 2014-06-20
Category : Business & Economics
ISBN : 9781118594513

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Handbook in Monte Carlo Simulation by Paolo Brandimarte Pdf

An accessible treatment of Monte Carlo methods, techniques, and applications in the field of finance and economics Providing readers with an in-depth and comprehensive guide, the Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics presents a timely account of the applicationsof Monte Carlo methods in financial engineering and economics. Written by an international leading expert in thefield, the handbook illustrates the challenges confronting present-day financial practitioners and provides various applicationsof Monte Carlo techniques to answer these issues. The book is organized into five parts: introduction andmotivation; input analysis, modeling, and estimation; random variate and sample path generation; output analysisand variance reduction; and applications ranging from option pricing and risk management to optimization. The Handbook in Monte Carlo Simulation features: An introductory section for basic material on stochastic modeling and estimation aimed at readers who may need a summary or review of the essentials Carefully crafted examples in order to spot potential pitfalls and drawbacks of each approach An accessible treatment of advanced topics such as low-discrepancy sequences, stochastic optimization, dynamic programming, risk measures, and Markov chain Monte Carlo methods Numerous pieces of R code used to illustrate fundamental ideas in concrete terms and encourage experimentation The Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics is a complete reference for practitioners in the fields of finance, business, applied statistics, econometrics, and engineering, as well as a supplement for MBA and graduate-level courses on Monte Carlo methods and simulation.

Author : Thomas M. Carsey,Jeffrey J. Harden
Publisher : SAGE Publications
Page : 304 pages
File Size : 51,8 Mb
Release : 2013-08-05
Category : Social Science
ISBN : 9781483324920

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Monte Carlo Simulation and Resampling Methods for Social Science by Thomas M. Carsey,Jeffrey J. Harden Pdf

Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and Jeffrey J. Harden, examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.

Author : David P. Landau,Kurt Binder
Publisher : Cambridge University Press
Page : 402 pages
File Size : 44,5 Mb
Release : 2000-08-17
Category : Mathematics
ISBN : 0521653665

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A Guide to Monte Carlo Simulations in Statistical Physics by David P. Landau,Kurt Binder Pdf

This book describes all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, as well as in related fields, such as polymer science and lattice gauge theory. The authors give a succinct overview of simple sampling methods and develop the importance sampling method. In addition they introduce quantum Monte Carlo methods, aspects of simulations of growth phenomena and other systems far from equilibrium, and the Monte Carlo Renormalization Group approach to critical phenomena. The book includes many applications, examples, and current references, and exercises to help the reader.

Author : Carl Graham,Denis Talay
Publisher : Springer Science & Business Media
Page : 260 pages
File Size : 46,6 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 : Gregory Rago
Publisher : Unknown
Page : 0 pages
File Size : 41,9 Mb
Release : 2015-02-11
Category : Monte Carlo method
ISBN : 1632402432

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Fundamentals and Applications of Monte Carlo Simulations by Gregory Rago Pdf

This book consists of up-to-date information regarding the fundamentals and applications of Monte Carlo simulations. The aim of this book is to provide information about the current developments and applications of Monte Carlo Simulation (MCS) to the readers. The vital feature of the MCS method is random sampling. The book describes how such a sampling method can be used to resolve complex problems or evaluate complicated systems in distinct science and engineering domains. Issues like uncertainty assessment, statistical estimation, variance reduction and optimization have been described in this book. Recent applications of MCS are illustrated in estimation of transition behavior of organic molecules, particle diffusion, financial systems modeling, healthcare practices, chemical reaction and kinetic simulation of biological data and biophysics. Field-specific background knowledge and utilities of MCS have been discussed to optimize the accessibility of this book. This book aims at unifying knowledge of the concept from distinct areas to promote novel applications and research endeavors of MCS.

Author : Jan F. Kiviet
Publisher : Foundations & Trends
Page : 185 pages
File Size : 50,9 Mb
Release : 2012
Category : Business & Economics
ISBN : 160198538X

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Monte Carlo Simulation for Econometricians by Jan F. Kiviet Pdf

Monte Carlo Simulation for Econometricians presents the fundamentals of Monte Carlo simulation (MCS), pointing to opportunities not often utilized in current practice, especially with regards to designing their general setup, controlling their accuracy, recognizing their shortcomings, and presenting their results in a coherent way. The author explores the properties of classic econometric inference techniques by simulation. The first three chapters focus on the basic tools of MCS. After treating the basic tools of MCS, Chapter 4 examines the crucial elements of analyzing the properties of asymptotic test procedures by MCS. Chapter 5 examines more general aspects of MCS, such as its history, possibilities to increase its efficiency and effectiveness, and whether synthetic random exogenous variables should be kept fixed over all the experiments or be treated as genuinely random and thus redrawn every replication. The simulation techniques that we discuss in the first five chapters are often addressed as naive or classic Monte Carlo methods. However, simulation can also be used not just for assessing the qualities of inference techniques, but also directly for obtaining inference in practice from empirical data. Various advanced inference techniques have been developed which incorporate simulation techniques. An early example of this is Monte Carlo testing, which corresponds to the parametric bootstrap technique. Chapter 6 highlights such techniques and presents a few examples of (semi-)parametric bootstrap techniques. This chapter also demonstrates that the bootstrap is not an alternative to MCS but just another practical inference technique, which uses simulation to produce econometric inference. Each chapter includes exercises allowing the reader to immerse in performing and interpreting MCS studies. The material has been used extensively in courses for undergraduate and graduate students. The various chapters all contain illustrations which throw light on what uses can be made from MCS to discover the finite sample properties of a broad range of alternative econometric methods with a focus on the rather basic models and techniques.

Author : Dirk P. Kroese,Thomas Taimre,Zdravko I. Botev
Publisher : John Wiley & Sons
Page : 627 pages
File Size : 49,8 Mb
Release : 2013-06-06
Category : Mathematics
ISBN : 9781118014950

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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.

Author : G.I. Marchuk,G.A. Mikhailov,M.A. Nazareliev,R.A. Darbinjan,B.A. Kargin,B.S. Elepov
Publisher : Springer
Page : 218 pages
File Size : 42,5 Mb
Release : 2013-04-17
Category : Science
ISBN : 9783540352372

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The Monte Carlo Methods in Atmospheric Optics by G.I. Marchuk,G.A. Mikhailov,M.A. Nazareliev,R.A. Darbinjan,B.A. Kargin,B.S. Elepov Pdf

This monograph is devoted to urgent questions of the theory and applications of the Monte Carlo method for solving problems of atmospheric optics and hydrooptics. The importance of these problems has grown because of the increas ing need to interpret optical observations, and to estimate radiative balance precisely for weather forecasting. Inhomogeneity and sphericity of the atmos phere, absorption in atmospheric layers, multiple scattering and polarization of light, all create difficulties in solving these problems by traditional methods of computational mathematics. Particular difficulty arises when one must solve nonstationary problems of the theory of transfer of narrow beams that are connected with the estimation of spatial location and time characteristics of the radiation field. The most universal method for solving those problems is the Monte Carlo method, which is a numerical simulation of the radiative-transfer process. This process can be regarded as a Markov chain of photon collisions in a medium, which result in scattering or absorption. The Monte Carlo tech nique consists in computational simulation of that chain and in constructing statistical estimates of the desired functionals. The authors of this book have contributed to the development of mathemati cal methods of simulation and to the interpretation of optical observations. A series of general method using Monte Carlo techniques has been developed. The present book includes theories and algorithms of simulation. Numerical results corroborate the possibilities and give an impressive prospect of the applications of Monte Carlo methods.