Lectures On Monte Carlo Methods
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Lectures On Monte Carlo Methods
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Author : Neal Noah Madras
language : en
Publisher: American Mathematical Soc.
Release Date : 2002
Lectures On Monte Carlo Methods written by Neal Noah Madras and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Mathematics categories.
Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the ``curse of dimensionality'', which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathematical models that arise in diverse areas of application. The book is based on lectures in a graduate course given by the author. It examines theoretical properties of Monte Carlo methods as well as practical issues concerning their computer implementation and statistical analysis. The only formal prerequisite is an undergraduate course in probability. The book is intended to be accessible to students from a wide range of scientific backgrounds. Rather than being a detailed treatise, it covers the key topics of Monte Carlo methods to the depth necessary for a researcher to design, implement, and analyze a full Monte Carlo study of a mathematical or scientific problem. The ideas are illustrated with diverse running examples. There are exercises sprinkled throughout the text. The topics covered include computer generation of random variables, techniques and examples for variance reduction of Monte Carlo estimates, Markov chain Monte Carlo, and statistical analysis of Monte Carlo output.
Monte Carlo And Quasi Monte Carlo Methods
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Author : Bruno Tuffin
language : en
Publisher: Springer Nature
Release Date : 2020-05-01
Monte Carlo And Quasi Monte Carlo Methods written by Bruno Tuffin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-01 with Computers categories.
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.
Advanced Lectures On Machine Learning
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Author : Olivier Bousquet
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-09-02
Advanced Lectures On Machine Learning written by Olivier Bousquet and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-09-02 with Computers categories.
Machine Learning has become a key enabling technology for many engineering applications, investigating scientific questions and theoretical problems alike. To stimulate discussions and to disseminate new results, a summer school series was started in February 2002, the documentation of which is published as LNAI 2600. This book presents revised lectures of two subsequent summer schools held in 2003 in Canberra, Australia, and in Tübingen, Germany. The tutorial lectures included are devoted to statistical learning theory, unsupervised learning, Bayesian inference, and applications in pattern recognition; they provide in-depth overviews of exciting new developments and contain a large number of references. Graduate students, lecturers, researchers and professionals alike will find this book a useful resource in learning and teaching machine learning.
Quantum Monte Carlo Methods In Physics And Chemistry
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Author : M.P. Nightingale
language : en
Publisher: Springer Science & Business Media
Release Date : 1998-12-31
Quantum Monte Carlo Methods In Physics And Chemistry written by M.P. Nightingale and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-12-31 with Science categories.
In recent years there has been a considerable growth in interest in Monte Carlo methods, and quantum Monte Carlo methods in particlular. Clearly, the ever-increasing computational power available to researchers, has stimulated the development of improved algorithms, and almost all fields in computational physics and chemistry are affected by their applications. Here we just mention some fields that are covered in the lecture notes contained in this volume, viz. electronic structure studies of atoms, molecules and solids, nuclear structure, and low- or zero-temperature studies of strongly-correlated quantum systems, both of the continuum and lattice variety, and cooperative phenomena in classical systems. Although each area of application may have its own peculiarities, requiring specialized solutions, all share the same basic methodology. It was with the intention of bringing together researchers and students from these various areas that the NATO Advanced Study Institute on Quantum Monte Carlo Methods in Physics and Chemistry was held at Cornell University from 12 to 24 July, 1998. This book contains material presented at the Institute in a series of mini courses in quantum Monte Carlo methods. The program consisted of lectures predominantly of a pedagogical nature, and of more specialized seminars. The levels varied from introductory to advanced, and from basic methods to applications; the program was intended for an audience working towards the Ph.D. level and above. Despite the essentially pedagogic nature of the Institute, several of the lectures and seminars contained in this volume present recent developments not previously published.
Sequential Monte Carlo Methods In Practice
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Author : Arnaud Doucet
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Sequential Monte Carlo Methods In Practice written by Arnaud Doucet and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
Monte Carlo methods are revolutionising the on-line analysis of data in fields as diverse as financial modelling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo filters, particle filters and survial of the fittest, have made it possible to solve numerically many complex, non-standarard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modelling, neural networks,optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection, computer vision, semiconductor design, population biology, dynamic Bayesian networks, and time series analysis. This will be of great value to students, researchers and practicioners, who have some basic knowledge of probability. Arnaud Doucet received the Ph. D. degree from the University of Paris- XI Orsay in 1997. From 1998 to 2000, he conducted research at the Signal Processing Group of Cambridge University, UK. He is currently an assistant professor at the Department of Electrical Engineering of Melbourne University, Australia. His research interests include Bayesian statistics, dynamic models and Monte Carlo methods. Nando de Freitas obtained a Ph.D. degree in information engineering from Cambridge University in 1999. He is presently a research associate with the artificial intelligence group of the University of California at Berkeley. His main research interests are in Bayesian statistics and the application of on-line and batch Monte Carlo methods to machine learning.
Sequential Monte Carlo Methods For Nonlinear Discrete Time Filtering
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Author : Marcelo G. S. Bruno
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2013
Sequential Monte Carlo Methods For Nonlinear Discrete Time Filtering written by Marcelo G. S. Bruno and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computers categories.
In these notes, we introduce particle filtering as a recursive importance sampling method that approximates the minimum-mean-square-error (MMSE) estimate of a sequence of hidden state vectors in scenarios where the joint probability distribution of the states and the observations is non-Gaussian and, therefore, closed-form analytical expressions for the MMSE estimate are generally unavailable. We begin the notes with a review of Bayesian approaches to static (i.e., time-invariant) parameter estimation. In the sequel, we describe the solution to the problem of sequential state estimation in linear, Gaussian dynamic models, which corresponds to the well-known Kalman (or Kalman-Bucy) filter. Finally, we move to the general nonlinear, non-Gaussian stochastic filtering problem and present particle filtering as a sequential Monte Carlo approach to solve that problem in a statistically optimal way. We review several techniques to improve the performance of particle filters, including importance function optimization, particle resampling, Markov Chain Monte Carlo move steps, auxiliary particle filtering, and regularized particle filtering. We also discuss Rao-Blackwellized particle filtering as a technique that is particularly well-suited for many relevant applications such as fault detection and inertial navigation. Finally, we conclude the notes with a discussion on the emerging topic of distributed particle filtering using multiple processors located at remote nodes in a sensor network. Throughout the notes, we often assume a more general framework than in most introductory textbooks by allowing either the observation model or the hidden state dynamic model to include unknown parameters. In a fully Bayesian fashion, we treat those unknown parameters also as random variables. Using suitable dynamic conjugate priors, that approach can be applied then to perform joint state and parameter estimation.
Monte Carlo Methods In Finance
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Author : Peter Jäckel
language : de
Publisher: John Wiley & Sons
Release Date : 2002-04-03
Monte Carlo Methods In Finance written by Peter Jäckel and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-04-03 with Business & Economics categories.
Dieses Buch ist ein handlicher und praktischer Leitfaden zur Monte Carlo Simulation (MCS). Er gibt eine Einführung in Standardmethoden und fortgeschrittene Verfahren, um die zunehmende Komplexität derivativer Portfolios besser zu erfassen. Das hier behandelte Spektrum von MCS-Anwendungen reicht von der Preisbestimmung komplexerer Derivate, z.B. von amerikanischen und asiatischen Optionen, bis hin zur Messung des Value at Risk und zur Modellierung komplexer Marktdynamik. Anhand einer Vielzahl praktischer Beispiele wird erläutert, wie man Monte Carlo Methoden einsetzt. Dabei gehen die Autoren zunächst auf die Grundlagen und danach auf fortgeschrittene Techniken ein. Darüber hinaus geben sie nützliche Tipps und Hinweise für das Entwickeln und Arbeiten mit MCS-Methoden. Die Autoren sind Experten auf dem Gebiet der Monte Carlo Simulation und verfügen über langjährige Erfahrung im Umgang mit MCS-Methoden. Die Begleit-CD enthält Excel Muster Spreadsheets sowie VBA und C++ Code Snippets, die der Leser installieren und so mit den im Buch beschriebenen Beispiele frei experimentieren kann. "Monte Carlo Methods in Finance" - ein unverzichtbares Nachschlagewerk für quantitative Analysten, die bei der Bewertung von Optionspreisen und Riskmanagement auf Modelle zurückgreifen müssen.
Monte Carlo Methods In Statistical Physics
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Author : K. Murthy
language : en
Publisher: Universities Press
Release Date : 2004
Monte Carlo Methods In Statistical Physics written by K. Murthy and has been published by Universities Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
Monte Carlo simulations comprise a substantial part of the new and third major arm of investigation in the physical sciences that has emerged in recent times, to augment the traditional ones of experiment and theory. With the advent of high-speed digital computing, numerical simulations techniques like Monte Carlo have been very successful in extracting real world observations out of seemingly intractable theoretical models.
Monte Carlo Methods
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Author : Neal Noah Madras
language : en
Publisher: American Mathematical Soc.
Release Date : 2000-01-01
Monte Carlo Methods written by Neal Noah Madras and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01-01 with Mathematics categories.
This volume contains the proceedings of the Workshop on Monte Carlo Methods held at The Fields Institute for Research in Mathematical Sciences (Toronto, 1998). The workshop brought together researchers in physics, statistics, and probability. The papers in this volume - of the invited speakers and contributors to the poster session - represent the interdisciplinary emphasis of the conference. Monte Carlo methods have been used intensively in many branches of scientific inquiry. Markov chain methods have been at the forefront of much of this work, serving as the basis of many numerical studies in statistical physics and related areas since the Metropolis algorithm was introduced in 1953. Statisticians and theoretical computer scientists have used these methods in recent years, working on different fundamental research questions, yet using similar Monte Carlo methodology. This volume focuses on Monte Carlo methods that appear to have wide applicability and emphasizes new methods, practical applications and theoretical analysis. It will be of interest to researchers and graduate students who study and/or use Monte Carlo methods in areas of probability, statistics, theoretical physics, or computer science.
Quantum Monte Carlo Methods In Physics And Chemistry
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Author : M.P. Nightingale
language : en
Publisher: Springer Science & Business Media
Release Date : 1998-12-31
Quantum Monte Carlo Methods In Physics And Chemistry written by M.P. Nightingale and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-12-31 with Mathematics categories.
This book contains lectures on the basic theory and applications of quantum Monte Carlo methods, with contributions written by authorities in the field. Although tutorial in nature, it includes current developments. Both continuum systems and lattice models are covered. The applications include atomic, molecular, and solid state physics, statistical and low-temperature physics, and nuclear structure. Suitable for Ph.D. students and beyond.