Foundations And Methods Of Stochastic Simulation

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Foundations and Methods of Stochastic Simulation

Barry Nelson
Foundations and Methods of Stochastic Simulation Book PDF

Author : Barry Nelson
Publisher : Springer Science & Business Media
Page : 276 pages
File Size : 41,7 Mb
Release : 2013-01-31
Category : Business & Economics
ISBN : 9781461461609

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Foundations and Methods of Stochastic Simulation by Barry Nelson Pdf

This graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous treatment of the foundations of simulation and why it works. It introduces object-oriented programming for simulation, covers both the probabilistic and statistical basis for simulation in a rigorous but accessible manner (providing all necessary background material); and provides a modern treatment of experiment design and analysis that goes beyond classical statistics. The book emphasizes essential foundations throughout, rather than providing a compendium of algorithms and theorems and prepares the reader to use simulation in research as well as practice. The book is a rigorous, but concise treatment, emphasizing lasting principles but also providing specific training in modeling, programming and analysis. In addition to teaching readers how to do simulation, it also prepares them to use simulation in their research; no other book does this. An online solutions manual for end of chapter exercises is also be provided.​

Foundations and Methods of Stochastic Simulation

Barry L. Nelson,Linda Pei
Foundations and Methods of Stochastic Simulation Book PDF

Author : Barry L. Nelson,Linda Pei
Publisher : Springer Nature
Page : 323 pages
File Size : 50,9 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.

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 : 52,8 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.

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 : 46,6 Mb
Release : 2011-11-21
Category : Business & Economics
ISBN : 9780470722138

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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.

Simulation Statistical Foundations and Methodology

Anonim
Simulation Statistical Foundations and Methodology Book PDF

Author : Anonim
Publisher : Academic Press
Page : 322 pages
File Size : 46,5 Mb
Release : 1972-09-29
Category : Mathematics
ISBN : 0080956017

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Simulation Statistical Foundations and Methodology by Anonim Pdf

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. - Best operator approximation, - Non-Lagrange interpolation, - Generic Karhunen-Loeve transform - Generalised low-rank matrix approximation - Optimal data compression - Optimal nonlinear filtering

An Introduction to Stochastic Modeling

Howard M. Taylor,Samuel Karlin
An Introduction to Stochastic Modeling Book PDF

Author : Howard M. Taylor,Samuel Karlin
Publisher : Academic Press
Page : 410 pages
File Size : 52,9 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.

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 : 47,9 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

Modelling and Simulation

Louis G. Birta,Gilbert Arbez
Modelling and Simulation Book PDF

Author : Louis G. Birta,Gilbert Arbez
Publisher : Springer Science & Business Media
Page : 463 pages
File Size : 52,8 Mb
Release : 2007-09-07
Category : Computers
ISBN : 9781846286216

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Modelling and Simulation by Louis G. Birta,Gilbert Arbez Pdf

This book provides a balanced and integrated presentation of modelling and simulation activity for both Discrete Event Dynamic Systems (DEDS) and Continuous Time Dynamic Systems (CYDS). The authors establish a clear distinction between the activity of modelling and that of simulation, maintaining this distinction throughout. The text offers a novel project-oriented approach for developing the modelling and simulation methodology, providing a solid basis for demonstrating the dependency of model structure and granularity on project goals. Comprehensive presentation of the verification and validation activities within the modelling and simulation context is also shown.

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 : 40,8 Mb
Release : 2007-07-14
Category : Mathematics
ISBN : 9780387690339

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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.

Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology

Paola Lecca,Ian Laurenzi,Ferenc Jordan
Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology Book PDF

Author : Paola Lecca,Ian Laurenzi,Ferenc Jordan
Publisher : Elsevier
Page : 411 pages
File Size : 44,8 Mb
Release : 2013-04-09
Category : Mathematics
ISBN : 9781908818218

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Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology by Paola Lecca,Ian Laurenzi,Ferenc Jordan Pdf

Stochastic kinetic methods are currently considered to be the most realistic and elegant means of representing and simulating the dynamics of biochemical and biological networks. Deterministic versus stochastic modelling in biochemistry and systems biology introduces and critically reviews the deterministic and stochastic foundations of biochemical kinetics, covering applied stochastic process theory for application in the field of modelling and simulation of biological processes at the molecular scale. Following an overview of deterministic chemical kinetics and the stochastic approach to biochemical kinetics, the book goes onto discuss the specifics of stochastic simulation algorithms, modelling in systems biology and the structure of biochemical models. Later chapters cover reaction-diffusion systems, and provide an analysis of the Kinfer and BlenX software systems. The final chapter looks at simulation of ecodynamics and food web dynamics. Introduces mathematical concepts and formalisms of deterministic and stochastic modelling through clear and simple examples Presents recently developed discrete stochastic formalisms for modelling biological systems and processes Describes and applies stochastic simulation algorithms to implement a stochastic formulation of biochemical and biological kinetics

Stochastic Methods in Engineering

I. St Doltsinis
Stochastic Methods in Engineering Book PDF

Author : I. St Doltsinis
Publisher : WIT Press
Page : 379 pages
File Size : 47,5 Mb
Release : 2012
Category : Mathematics
ISBN : 9781845646264

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Stochastic Methods in Engineering by I. St Doltsinis Pdf

The increasing industrial demand for reliable quantification and management of uncertainty in product performance forces engineers to employ probabilistic models in analysis and design, a fact that has occasioned considerable research and development activities in the field. Notes on Stochastics eventually address the topic of computational stochastic mechanics. The single volume uniquely presents tutorials on essential probabilistics and statistics, recent finite element methods for stochastic analysis by Taylor series expansion as well as Monte Carlo simulation techniques. Design improvement and robust optimisation represent key issues as does reliability assessment. The subject is developed for solids and structures of elastic and elasto-plastic material, large displacements and material deformation processes; principles are transferable to various disciplines. A chapter is devoted to the statistical comparison of systems exhibiting random scatter. Where appropriate examples illustrate the theory, problems to solve appear instructive; applications are presented with relevance to engineering practice. The book, emanating from a university course, includes research and development in the field of computational stochastic analysis and optimization. It is intended for advanced students in engineering and for professionals who wish to extend their knowledge and skills in computational mechanics to the domain of stochastics. Contents: Introduction, Randomness, Structural analysis by Taylor series expansion, Design optimization, Robustness, Monte Carlo techniques for system response and design improvement, Reliability, Time variant phenomena, Material deformation processes, Analysis and comparison of data sets, Probability distribution of test functions.

27th European Symposium on Computer Aided Process Engineering

Anonim
27th European Symposium on Computer Aided Process Engineering Book PDF

Author : Anonim
Publisher : Elsevier
Page : 3064 pages
File Size : 49,8 Mb
Release : 2017-09-21
Category : Science
ISBN : 9780444639707

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27th European Symposium on Computer Aided Process Engineering by Anonim Pdf

27th European Symposium on Computer Aided Process Engineering, Volume 40 contains the papers presented at the 27th European Society of Computer-Aided Process Engineering (ESCAPE) event held in Barcelona, October 1-5, 2017. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries. Presents findings and discussions from the 27th European Society of Computer-Aided Process Engineering (ESCAPE) event

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 : 54,5 Mb
Release : 2013-06-06
Category : Mathematics
ISBN : 1118014952

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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.

Ambit Stochastics

Ole E. Barndorff-Nielsen,Fred Espen Benth,Almut E. D. Veraart
Ambit Stochastics Book PDF

Author : Ole E. Barndorff-Nielsen,Fred Espen Benth,Almut E. D. Veraart
Publisher : Springer
Page : 402 pages
File Size : 43,7 Mb
Release : 2018-11-01
Category : Mathematics
ISBN : 9783319941295

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Ambit Stochastics by Ole E. Barndorff-Nielsen,Fred Espen Benth,Almut E. D. Veraart Pdf

Drawing on advanced probability theory, Ambit Stochastics is used to model stochastic processes which depend on both time and space. This monograph, the first on the subject, provides a reference for this burgeoning field, complete with the applications that have driven its development. Unique to Ambit Stochastics are ambit sets, which allow the delimitation of space-time to a zone of interest, and ambit fields, which are particularly well-adapted to modelling stochastic volatility or intermittency. These attributes lend themselves notably to applications in the statistical theory of turbulence and financial econometrics. In addition to the theory and applications of Ambit Stochastics, the book also contains new theory on the simulation of ambit fields and a comprehensive stochastic integration theory for Volterra processes in a non-semimartingale context. Written by pioneers in the subject, this book will appeal to researchers and graduate students interested in empirical stochastic modelling.

Stochastic Simulation

Brian D. Ripley
Stochastic Simulation Book PDF

Author : Brian D. Ripley
Publisher : John Wiley & Sons
Page : 237 pages
File Size : 53,5 Mb
Release : 2009-09-25
Category : Mathematics
ISBN : 9780470317389

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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.