Monte Carlo Strategies in Scientific Computing

Monte Carlo Strategies in Scientific Computing PDF Author: Jun S. Liu
Publisher: Springer Science & Business Media
ISBN: 0387763716
Category : Mathematics
Languages : en
Pages : 350

Book Description
This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared. Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians. It can also be used as a textbook for a graduate-level course on Monte Carlo methods.

Introducing Monte Carlo Methods with R

Introducing Monte Carlo Methods with R PDF Author: Christian Robert
Publisher: Springer Science & Business Media
ISBN: 1441915753
Category : Computers
Languages : en
Pages : 297

Book Description
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.

Advanced Markov Chain Monte Carlo Methods

Advanced Markov Chain Monte Carlo Methods PDF Author: Faming Liang
Publisher: John Wiley & Sons
ISBN: 1119956803
Category : Mathematics
Languages : en
Pages : 308

Book Description
Markov Chain Monte Carlo (MCMC) methods are now an indispensable tool in scientific computing. This book discusses recent developments of MCMC methods with an emphasis on those making use of past sample information during simulations. The application examples are drawn from diverse fields such as bioinformatics, machine learning, social science, combinatorial optimization, and computational physics. Key Features: Expanded coverage of the stochastic approximation Monte Carlo and dynamic weighting algorithms that are essentially immune to local trap problems. A detailed discussion of the Monte Carlo Metropolis-Hastings algorithm that can be used for sampling from distributions with intractable normalizing constants. Up-to-date accounts of recent developments of the Gibbs sampler. Comprehensive overviews of the population-based MCMC algorithms and the MCMC algorithms with adaptive proposals. This book can be used as a textbook or a reference book for a one-semester graduate course in statistics, computational biology, engineering, and computer sciences. Applied or theoretical researchers will also find this book beneficial.

Scientific Computing with Case Studies

Scientific Computing with Case Studies PDF Author: Dianne P. O'Leary
Publisher: SIAM
ISBN: 0898716667
Category : Mathematics
Languages : en
Pages : 376

Book Description
This book is a practical guide to the numerical solution of linear and nonlinear equations, differential equations, optimization problems, and eigenvalue problems. It treats standard problems and introduces important variants such as sparse systems, differential-algebraic equations, constrained optimization, Monte Carlo simulations, and parametric studies. Stability and error analysis are emphasized, and the Matlab algorithms are grounded in sound principles of software design and understanding of machine arithmetic and memory management. Nineteen case studies provide experience in mathematical modeling and algorithm design, motivated by problems in physics, engineering, epidemiology, chemistry, and biology. The topics included go well beyond the standard first-course syllabus, introducing important problems such as differential-algebraic equations and conic optimization problems, and important solution techniques such as continuation methods. The case studies cover a wide variety of fascinating applications, from modeling the spread of an epidemic to determining truss configurations.

Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing PDF Author: Harald Niederreiter
Publisher: Springer Science & Business Media
ISBN: 1461225523
Category : Mathematics
Languages : en
Pages : 391

Book Description
Scientists and engineers are increasingly making use of simulation methods to solve problems which are insoluble by analytical techniques. Monte Carlo methods which make use of probabilistic simulations are frequently used in areas such as numerical integration, complex scheduling, queueing networks, and large-dimensional simulations. This collection of papers arises from a conference held at the University of Nevada, Las Vegas, in 1994. The conference brought together researchers across a range of disciplines whose interests include the theory and application of these methods. This volume provides a timely survey of this field and the new directions in which the field is moving.

Monte Carlo and Quasi-Monte Carlo Methods

Monte Carlo and Quasi-Monte Carlo Methods PDF Author: Art B. Owen
Publisher: Springer
ISBN: 3319914367
Category : Computers
Languages : en
Pages : 476

Book Description
This book presents the refereed proceedings of the Twelfth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at Stanford University (California) in August 2016. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising in particular, in finance, statistics, computer graphics and the solution of PDEs.

Monte Carlo Methods

Monte Carlo Methods PDF Author: Thomas Michael Keegan
Publisher: Hassell Street Press
ISBN: 9781019364451
Category :
Languages : en
Pages : 0

Book Description
This book provides a comprehensive guide to the principles and applications of Monte Carlo methods in scientific computing. With clear explanations and examples drawn from a variety of fields, Thomas Michael Keegan offers readers an accessible introduction to this powerful tool for solving problems in physics, engineering, mathematics, and other disciplines. This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

Monte Carlo and Quasi-Monte Carlo Methods 2010

Monte Carlo and Quasi-Monte Carlo Methods 2010 PDF Author: Leszek Plaskota
Publisher: Springer
ISBN: 9783642274411
Category : Mathematics
Languages : en
Pages : 732

Book Description
This book represents the refereed proceedings of the Ninth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Warsaw (Poland) in August 2010. These biennial conferences are major events for Monte Carlo and the premiere event for quasi-Monte Carlo research. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. The reader will be provided with information on latest developments in these very active areas. The book is an excellent reference for theoreticians and practitioners interested in solving high-dimensional computational problems arising, in particular, in finance and statistics.
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