Download or read book Multilevel Monte Carlo Methods for Stochastic Elliptic Multiscale PDEs written by Assyr Abdulle (Mathematiker) 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 and Quasi Monte Carlo Methods written by Bruno Tuffin and published by Springer Nature. This book was released on 2020-05-01 with total page 533 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed proceedings of the 13th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Rennes, France, and organized by Inria, in July 2018. 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 and computer graphics.
Download or read book Numerical Methods for Stochastic Partial Differential Equations with White Noise written by Zhongqiang Zhang and published by Springer. This book was released on 2017-09-01 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers numerical methods for stochastic partial differential equations with white noise using the framework of Wong-Zakai approximation. The book begins with some motivational and background material in the introductory chapters and is divided into three parts. Part I covers numerical stochastic ordinary differential equations. Here the authors start with numerical methods for SDEs with delay using the Wong-Zakai approximation and finite difference in time. Part II covers temporal white noise. Here the authors consider SPDEs as PDEs driven by white noise, where discretization of white noise (Brownian motion) leads to PDEs with smooth noise, which can then be treated by numerical methods for PDEs. In this part, recursive algorithms based on Wiener chaos expansion and stochastic collocation methods are presented for linear stochastic advection-diffusion-reaction equations. In addition, stochastic Euler equations are exploited as an application of stochastic collocation methods, where a numerical comparison with other integration methods in random space is made. Part III covers spatial white noise. Here the authors discuss numerical methods for nonlinear elliptic equations as well as other equations with additive noise. Numerical methods for SPDEs with multiplicative noise are also discussed using the Wiener chaos expansion method. In addition, some SPDEs driven by non-Gaussian white noise are discussed and some model reduction methods (based on Wick-Malliavin calculus) are presented for generalized polynomial chaos expansion methods. Powerful techniques are provided for solving stochastic partial differential equations. This book can be considered as self-contained. Necessary background knowledge is presented in the appendices. Basic knowledge of probability theory and stochastic calculus is presented in Appendix A. In Appendix B some semi-analytical methods for SPDEs are presented. In Appendix C an introduction to Gauss quadrature is provided. In Appendix D, all the conclusions which are needed for proofs are presented, and in Appendix E a method to compute the convergence rate empirically is included. In addition, the authors provide a thorough review of the topics, both theoretical and computational exercises in the book with practical discussion of the effectiveness of the methods. Supporting Matlab files are made available to help illustrate some of the concepts further. Bibliographic notes are included at the end of each chapter. This book serves as a reference for graduate students and researchers in the mathematical sciences who would like to understand state-of-the-art numerical methods for stochastic partial differential equations with white noise.
Download or read book Monte Carlo and Quasi Monte Carlo Methods written by Ronald Cools and published by Springer. This book was released on 2016-06-13 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. 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 and computer graphics.
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 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 Proceedings Of The International Congress Of Mathematicians 2018 Icm 2018 In 4 Volumes written by Sirakov Boyan and published by World Scientific. This book was released on 2019-02-27 with total page 5396 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Proceedings of the ICM publishes the talks, by invited speakers, at the conference organized by the International Mathematical Union every 4 years. It covers several areas of Mathematics and it includes the Fields Medal and Nevanlinna, Gauss and Leelavati Prizes and the Chern Medal laudatios.
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 Theory Numerics and Applications of Hyperbolic Problems II written by Christian Klingenberg and published by Springer. This book was released on 2018-06-27 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second of two volumes, this edited proceedings book features research presented at the XVI International Conference on Hyperbolic Problems held in Aachen, Germany in summer 2016. It focuses on the theoretical, applied, and computational aspects of hyperbolic partial differential equations (systems of hyperbolic conservation laws, wave equations, etc.) and of related mathematical models (PDEs of mixed type, kinetic equations, nonlocal or/and discrete models) found in the field of applied sciences.
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 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 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 and Quasi Monte Carlo Methods 2012 written by Josef Dick and published by Springer Science & Business Media. This book was released on 2013-12-05 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book represents the refereed proceedings of the Tenth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of New South Wales (Australia) in February 2012. 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, statistics and computer graphics.
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 Mixing Monte Carlo and Partial Differential Equation Methods For Multi dimensional Optimal Stopping Problems Under Stochastic Volatility written by David Farahany and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we develop a numerical approach for solving multi-dimensional optimal stopping problems (OSPs) under stochastic volatility (SV) that combines least squares Monte Carlo (LSMC) with partial differential equation (PDE) techniques. The algorithm provides dimensional reduction from the PDE and regression perspective along with variance and dimensional reduction from the MC perspective. In Chapter 2, we begin by laying the mathematical foundation of mixed MC-PDE techniques for OSPs. Next, we show the basic mechanics of the algorithm and, under certain mild assumptions, prove it converges almost surely. We apply the algorithm to the one dimensional Heston model and demonstrate that the hybrid algorithm outperforms traditional LSMC techniques in terms of both estimating prices and optimal exercise boundaries (OEBs). In Chapter 3 we describe methods for reducing the complexity and run time of the algorithm along with techniques for computing sensitivities. To reduce the complexity, we apply two methods: clustering via sufficient statistics and multi-level Monte Carlo (mlMC)/multi-grids. While the clustering method allows us to reduce computational run times by a third for high dimensional problems, mlMC provides an order of magnitude reduction in complexity. To compute sensitivities, we employ a grid based method for derivatives with respect to the asset, S, and an MC method that uses initial dispersions for sensitivities with respect to variance, v. To test our approximations and computation of sensitivities, we revisit the one-dimensional Heston model and find our approximations introduce little-to-no error and that our computation of sensitivities is highly accurate in comparison to standard LSMC. To demonstrate the utility of our new computational techniques, we apply the hybrid algorithm to the multi-dimensional Heston model and show that the algorithm is highly accurate in terms of estimating prices, OEBs, and sensitivities, especially in comparison to standard LSMC. In Chapter 4 we highlight the importance of multi-factor SV models and apply our hybrid algorithm to two specific examples: the Double Heston model and a mean-reverting commodity model with jumps. Again, we were able to obtain low variance estimates of the prices, OEBs, and sensitivities.
Download or read book An Introduction to Computational Stochastic PDEs written by Gabriel J. Lord and published by Cambridge University Press. This book was released on 2014-08-11 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a practical presentation of stochastic partial differential equations arising in physical applications and their numerical approximation.
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.
