Download or read book A Multi level Monte Carlo Algorithm for L vy Driven Stochastic Differential Equations written by Steffen Dereich and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multilevel Monte Carlo Simulation for Stochastic Differential Equations Driven by L vy Processes written by Sangmeng Li and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monte Carlo Methods and Stochastic Processes written by Emmanuel Gobet and published by CRC Press. This book was released on 2016-09-15 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Multilevel Monte Carlo Methods with Applications to Biochemical Models written by and published by . This book was released on 2015 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we study multilevel Monte Carlo simulation methods and applications to different types of stochastic dynamical models. This dissertation focuses on three selected topics. Firstly, tau-leaping is a popular discretization method for generating approximate paths of continuous time, discrete space Markov chains, notably for biochemical reaction systems. To compute expected values in this context, an appropriate multilevel Monte Carlo form of tau-leaping has been shown to improve efficiency dramatically. The contribution for this topic is deriving new analytic results concerning the computational complexity of multilevel Monte Carlo tau-leaping that are significantly sharper than previous ones. The key feature of the analysis that allows for the sharper bounds is that when comparing relevant pairs of processes we analyze the vari- ance of their difference directly rather than bounding via the second moment. Secondly, we consider the problem of numerically estimating expectations of solutions to stochastic differential equations driven by Brownian motions in the small noise regime. Our complexity analysis shows multilevel Monte Carlo can improve on the complexity of standard Monte Carlo by a factor [epsilon], where [epsilon] is the desired accuracy. The take-home message is that, under reasonable assumptions, a basic Euler-Maruyama discretization leads to optimal asymptotic computational complexity when used in a multilevel setting. Thirdly, we analyze and compare the computational complexity of different simulation strategies for classically scaled continuous time Markov chains. We provide numerical examples demonstrating our main conclusions. The three topics have appeared in a series of three papers published or under review.
Download or read book Applied Stochastic Differential Equations written by Simo Särkkä and published by Cambridge University Press. This book was released on 2019-05-02 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.
Download or read book Estimating the Parameters of Stochastic Differential Equations by Monte Carlo Methods written by A. Stan Hurn and published by . This book was released on 1995 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monte Carlo and Quasi Monte Carlo Methods 2006 written by Alexander Keller and published by Springer Science & Business Media. This book was released on 2007-12-30 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed proceedings of the Seventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, held in Ulm, Germany, in August 2006. The proceedings include carefully selected papers on many aspects of Monte Carlo and quasi-Monte Carlo methods and their applications. They also provide information on current research in these very active areas.
Download or read book Multilevel Monte Carlo Method for Parabolic Stochastic Partial Differential Equations written by Andrea Barth and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Monte Carlo Methods for Transport and Diffusion Equations written by Bernard Lapeyre and published by OUP Oxford. This book was released on 2003 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is used by for the resolution of partial differential equations, trasnport equations, the Boltzmann equation and the parabolic equations of diffusion.
Download or read book Multi level Monte Carlo Algorithms for L vy driven SDEs with Gaussian Correction written by Steffen Dereich and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advanced Simulation Based Methods for Optimal Stopping and Control written by Denis Belomestny and published by Springer. This book was released on 2018-01-31 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an advanced guide to optimal stopping and control, focusing on advanced Monte Carlo simulation and its application to finance. Written for quantitative finance practitioners and researchers in academia, the book looks at the classical simulation based algorithms before introducing some of the new, cutting edge approaches under development.
Download or read book Monte Carlo Methods And Parallel Algorithms International Youth Workshop written by I Dimov and published by World Scientific. This book was released on 1991-01-31 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings present recent advances in the Monte Carlo methods, covering theoretical aspects, a wide range of applications in solving problems, and parallel algorithms for Monte Carlo computations.
Download or read book Multilevel Monte Carlo Method with Applications to Stocastic Partial Differential Equations written by Andrea Barth and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monte Carlo Methods for Partial Differential Equations With Applications to Electronic Design Automation written by Wenjian Yu and published by Springer Nature. This book was released on 2022-09-02 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Monte Carlo method is one of the top 10 algorithms in the 20th century. This book is focusing on the Monte Carlo method for solving deterministic partial differential equations (PDEs), especially its application to electronic design automation (EDA) problems. Compared with the traditional method, the Monte Carlo method is more efficient when point values or linear functional of the solution are needed, and has the advantages on scalability, parallelism, and stability of accuracy. This book presents a systematic introduction to the Monte Carlo method for solving major kinds of PDEs, and the detailed explanation of relevant techniques for EDA problems especially the cutting-edge algorithms of random walk based capacitance extraction. It includes about 100 figures and 50 tables, and brings the reader a close look to the newest research results and the sophisticated algorithmic skills in Monte Carlo simulation software.
Download or read book Monte Carlo Methods written by Malvin H. Kalos and published by John Wiley & Sons. This book was released on 2009-06-10 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introduction to Monte Carlo methods seeks to identify and study the unifying elements that underlie their effective application. Initial chapters provide a short treatment of the probability and statistics needed as background, enabling those without experience in Monte Carlo techniques to apply these ideas to their research. The book focuses on two basic themes: The first is the importance of random walks as they occur both in natural stochastic systems and in their relationship to integral and differential equations. The second theme is that of variance reduction in general and importance sampling in particular as a technique for efficient use of the methods. Random walks are introduced with an elementary example in which the modeling of radiation transport arises directly from a schematic probabilistic description of the interaction of radiation with matter. Building on this example, the relationship between random walks and integral equations is outlined. The applicability of these ideas to other problems is shown by a clear and elementary introduction to the solution of the Schrödinger equation by random walks. The text includes sample problems that readers can solve by themselves to illustrate the content of each chapter. This is the second, completely revised and extended edition of the successful monograph, which brings the treatment up to date and incorporates the many advances in Monte Carlo techniques and their applications, while retaining the original elementary but general approach.
Download or read book Adaptive Multi Level Monte Carlo and Stochastic Collocation Methods for Hyperbolic Partial Differential Equations with Random Data on Networks written by Elisa Strauch and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monte Carlo Methods for Stochastic Differential Equations and Their Applications written by Andrew Bradford Leach and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We introduce computationally efficient Monte Carlo methods for studying the statistics of stochastic differential equations in two distinct settings. In the first, we derive importance sampling methods for data assimilation when the noise in the model and observations are small. The methods are formulated in discrete time, where the "posterior" distribution we want to sample from can be analyzed in an accessible small noise expansion. We show that a "symmetrization" procedure akin to antithetic coupling can improve the order of accuracy of the sampling methods, which is illustrated with numerical examples. In the second setting, we develop "stochastic continuation" methods to estimate level sets for statistics of stochastic differential equations with respect to their parameters. We adapt Keller's Pseudo-Arclength continuation method to this setting using stochastic approximation, and generalized least squares regression. Furthermore, we show that the methods can be improved through the use of coupling methods to reduce the variance of the derivative estimates that are involved.
