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Author : A. Stan Hurn,K. A. Lindsay
Publisher : Unknown
Page : 7 pages
File Size : 44,5 Mb
Release : 1995
Category : Stochastic differential equations
ISBN : 0732512271
Author : Carl Graham,Denis Talay
Publisher : Springer Science & Business Media
Page : 260 pages
File Size : 50,7 Mb
Release : 2013-07-16
Category : Mathematics
ISBN : 9783642393631
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 : Alexander Keller,Stefan Heinrich,Harald Niederreiter
Publisher : Springer Science & Business Media
Page : 698 pages
File Size : 50,5 Mb
Release : 2007-12-30
Category : Mathematics
ISBN : 9783540744962
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.
Author : G. A. Mikhailov
Publisher : Walter de Gruyter GmbH & Co KG
Page : 196 pages
File Size : 42,5 Mb
Release : 2018-11-05
Category : Mathematics
ISBN : 9783110941951
No detailed description available for "Parametric Estimates by the Monte Carlo Method".
Author : N El Karoui,Laurent Mazliak
Publisher : CRC Press
Page : 236 pages
File Size : 44,8 Mb
Release : 1997-01-17
Category : Mathematics
ISBN : 0582307333
This book presents the texts of seminars presented during the years 1995 and 1996 at the Université Paris VI and is the first attempt to present a survey on this subject. Starting from the classical conditions for existence and unicity of a solution in the most simple case-which requires more than basic stochartic calculus-several refinements on the hypotheses are introduced to obtain more general results.
Author : James E. Gentle
Publisher : Springer Science & Business Media
Page : 387 pages
File Size : 40,7 Mb
Release : 2004-09-14
Category : Computers
ISBN : 9780387001784
Monte Carlo simulation has become one of the most important tools in all fields of science. Simulation methodology relies on a good source of numbers that appear to be random. These "pseudorandom" numbers must pass statistical tests just as random samples would. Methods for producing pseudorandom numbers and transforming those numbers to simulate samples from various distributions are among the most important topics in statistical computing. This book surveys techniques of random number generation and the use of random numbers in Monte Carlo simulation. The book covers basic principles, as well as newer methods such as parallel random number generation, nonlinear congruential generators, quasi Monte Carlo methods, and Markov chain Monte Carlo. The best methods for generating random variates from the standard distributions are presented, but also general techniques useful in more complicated models and in novel settings are described. The emphasis throughout the book is on practical methods that work well in current computing environments. The book includes exercises and can be used as a test or supplementary text for various courses in modern statistics. It could serve as the primary test for a specialized course in statistical computing, or as a supplementary text for a course in computational statistics and other areas of modern statistics that rely on simulation. The book, which covers recent developments in the field, could also serve as a useful reference for practitioners. Although some familiarity with probability and statistics is assumed, the book is accessible to a broad audience. The second edition is approximately 50% longer than the first edition. It includes advances in methods for parallel random number generation, universal methods for generation of nonuniform variates, perfect sampling, and software for random number generation.
Author : Mathieu Kessler,Alexander Lindner,Michael Sorensen
Publisher : CRC Press
Page : 507 pages
File Size : 43,8 Mb
Release : 2012-05-17
Category : Mathematics
ISBN : 9781439849767
The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to th
Author : Simo Särkkä,Arno Solin
Publisher : Cambridge University Press
Page : 327 pages
File Size : 51,6 Mb
Release : 2019-05-02
Category : Business & Economics
ISBN : 9781316510087
With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.
Author : Kęstutis Kubilius,Yuliya Mishura,Kostiantyn Ralchenko
Publisher : Springer
Page : 390 pages
File Size : 52,9 Mb
Release : 2018-01-04
Category : Mathematics
ISBN : 9783319710303
This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years now, standard Brownian motion has been (and still remains) a popular model of randomness used to investigate processes in the natural sciences, financial markets, and the economy. The substantial limitation in the use of stochastic diffusion models with Brownian motion is due to the fact that the motion has independent increments, and, therefore, the random noise it generates is “white,” i.e., uncorrelated. However, many processes in the natural sciences, computer networks and financial markets have long-term or short-term dependences, i.e., the correlations of random noise in these processes are non-zero, and slowly or rapidly decrease with time. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion. Therefore, the book constructs diffusion models with memory and provides simple and suitable parameter estimation methods in these models, making it a valuable resource for all researchers in this field. The book is addressed to specialists and researchers in the theory and statistics of stochastic processes, practitioners who apply statistical methods of parameter estimation, graduate and post-graduate students who study mathematical modeling and statistics.
Author : Harald Niederreiter,Denis Talay
Publisher : Springer Science & Business Media
Page : 506 pages
File Size : 55,5 Mb
Release : 2006-02-08
Category : Mathematics
ISBN : 9783540311867
This book represents the refereed proceedings of the Sixth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing and of the Second International Conference on Monte Carlo and Probabilistic Methods for Partial Differential Equations. These conferences were held jointly at Juan-les-Pins (France) in June 2004. The proceedings include carefully selected papers on many aspects of Monte Carlo methods, quasi-Monte Carlo methods, and the numerical solution of partial differential equations. The reader will be informed about current research in these very active areas.
Author : Simo Särkkä
Publisher : Cambridge University Press
Page : 255 pages
File Size : 45,9 Mb
Release : 2013-09-05
Category : Computers
ISBN : 9781107030657
A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.
Author : Anthony Almudevar,David Oakes,Jack Hall
Publisher : Springer Nature
Page : 361 pages
File Size : 51,8 Mb
Release : 2020-03-11
Category : Medical
ISBN : 9783030346751
This book commemorates the scientific contributions of distinguished statistician, Andrei Yakovlev. It reflects upon Dr. Yakovlev’s many research interests including stochastic modeling and the analysis of micro-array data, and throughout the book it emphasizes applications of the theory in biology, medicine and public health. The contributions to this volume are divided into two parts. Part A consists of original research articles, which can be roughly grouped into four thematic areas: (i) branching processes, especially as models for cell kinetics, (ii) multiple testing issues as they arise in the analysis of biologic data, (iii) applications of mathematical models and of new inferential techniques in epidemiology, and (iv) contributions to statistical methodology, with an emphasis on the modeling and analysis of survival time data. Part B consists of methodological research reported as a short communication, ending with some personal reflections on research fields associated with Andrei and on his approach to science. The Appendix contains an abbreviated vitae and a list of Andrei’s publications, complete as far as we know. The contributions in this book are written by Dr. Yakovlev’s collaborators and notable statisticians including former presidents of the Institute of Mathematical Statistics and of the Statistics Section of the AAAS. Dr. Yakovlev’s research appeared in four books and almost 200 scientific papers, in mathematics, statistics, biomathematics and biology journals. Ultimately this book offers a tribute to Dr. Yakovlev’s work and recognizes the legacy of his contributions in the biostatistics community.
Author : Mircea Grigoriu
Publisher : Springer Science & Business Media
Page : 794 pages
File Size : 54,9 Mb
Release : 2002-09-24
Category : Mathematics
ISBN : 0817642420
Chapters 6-9 present methods for solving problems defined by equations with deterministic and/or random coefficients and deterministic and/or stochastic inputs. The Monte Carlo simulation is used extensively throughout to clarify advanced theoretical concepts and provide solutions to a broad range of stochastic problems.".
Author : David Barber,A. Taylan Cemgil,Silvia Chiappa
Publisher : Cambridge University Press
Page : 432 pages
File Size : 48,8 Mb
Release : 2011-08-11
Category : Computers
ISBN : 9780521196765
The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.
Author : Art B. Owen,Peter W. Glynn
Publisher : Springer
Page : 479 pages
File Size : 49,8 Mb
Release : 2018-07-03
Category : Computers
ISBN : 9783319914367
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.