Download or read book An Overview of the Monte Carlo Methods Codes Applications Group written by and published by . This book was released on 2016 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report delivers first principle Monte Carlo methods, production quality codes, and radiation transport based computational and experimental assessment.
Download or read book Monte Carlo written by George Fishman and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 721 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apart from a thorough exploration of all the important concepts, this volume includes over 75 algorithms, ready for putting into practice. The book also contains numerous hands-on implementations of selected algorithms to demonstrate applications in realistic settings. Readers are assumed to have a sound understanding of calculus, introductory matrix analysis, and intermediate statistics, but otherwise the book is self-contained. Suitable for graduates and undergraduates in mathematics and engineering, in particular operations research, statistics, and computer science.
Download or read book Theory Application and Implementation of Monte Carlo Method in Science and Technology written by Pooneh Saidi Bidokhti and published by BoD – Books on Demand. This book was released on 2019-12-18 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Monte Carlo method is a numerical technique to model the probability of all possible outcomes in a process that cannot easily be predicted due to the interference of random variables. It is a technique used to understand the impact of risk, uncertainty, and ambiguity in forecasting models. However, this technique is complicated by the amount of computer time required to achieve sufficient precision in the simulations and evaluate their accuracy. This book discusses the general principles of the Monte Carlo method with an emphasis on techniques to decrease simulation time and increase accuracy.
Download or read book Handbook of Monte Carlo Methods written by Dirk P. Kroese and published by John Wiley & Sons. This book was released on 2013-06-06 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications More and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the Monte Carlo approach. Handbook of Monte Carlo Methods provides the theory, algorithms, and applications that helps provide a thorough understanding of the emerging dynamics of this rapidly-growing field. The authors begin with a discussion of fundamentals such as how to generate random numbers on a computer. Subsequent chapters discuss key Monte Carlo topics and methods, including: Random variable and stochastic process generation Markov chain Monte Carlo, featuring key algorithms such as the Metropolis-Hastings method, the Gibbs sampler, and hit-and-run Discrete-event simulation Techniques for the statistical analysis of simulation data including the delta method, steady-state estimation, and kernel density estimation Variance reduction, including importance sampling, latin hypercube sampling, and conditional Monte Carlo Estimation of derivatives and sensitivity analysis Advanced topics including cross-entropy, rare events, kernel density estimation, quasi Monte Carlo, particle systems, and randomized optimization The presented theoretical concepts are illustrated with worked examples that use MATLAB®, a related Web site houses the MATLAB® code, allowing readers to work hands-on with the material and also features the author's own lecture notes on Monte Carlo methods. Detailed appendices provide background material on probability theory, stochastic processes, and mathematical statistics as well as the key optimization concepts and techniques that are relevant to Monte Carlo simulation. Handbook of Monte Carlo Methods is an excellent reference for applied statisticians and practitioners working in the fields of engineering and finance who use or would like to learn how to use Monte Carlo in their research. It is also a suitable supplement for courses on Monte Carlo methods and computational statistics at the upper-undergraduate and graduate levels.
Download or read book Monte Carlo Methods in Statistical Physics written by Kurt Binder and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the seven years since this volume first appeared. there has been an enormous expansion of the range of problems to which Monte Carlo computer simulation methods have been applied. This fact has already led to the addition of a companion volume ("Applications of the Monte Carlo Method in Statistical Physics", Topics in Current Physics. Vol . 36), edited in 1984, to this book. But the field continues to develop further; rapid progress is being made with respect to the implementation of Monte Carlo algorithms, the construction of special-purpose computers dedicated to exe cute Monte Carlo programs, and new methods to analyze the "data" generated by these programs. Brief descriptions of these and other developments, together with numerous addi tional references, are included in a new chapter , "Recent Trends in Monte Carlo Simulations" , which has been written for this second edition. Typographical correc tions have been made and fuller references given where appropriate, but otherwise the layout and contents of the other chapters are left unchanged. Thus this book, together with its companion volume mentioned above, gives a fairly complete and up to-date review of the field. It is hoped that the reduced price of this paperback edition will make it accessible to a wide range of scientists and students in the fields to which it is relevant: theoretical phYSics and physical chemistry , con densed-matter physics and materials science, computational physics and applied mathematics, etc.
Download or read book The Monte Carlo Methods written by Abdo Abou Jaoudé and published by BoD – Books on Demand. This book was released on 2022-03-09 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: In applied mathematics, the name Monte Carlo is given to the method of solving problems by means of experiments with random numbers. This name, after the casino at Monaco, was first applied around 1944 to the method of solving deterministic problems by reformulating them in terms of a problem with random elements, which could then be solved by large-scale sampling. But, by extension, the term has come to mean any simulation that uses random numbers. Monte Carlo methods have become among the most fundamental techniques of simulation in modern science. This book is an illustration of the use of Monte Carlo methods applied to solve specific problems in mathematics, engineering, physics, statistics, and science in general.
Download or read book Forecasting in Mathematics written by Abdo Abou Jaoude and published by BoD – Books on Demand. This book was released on 2021-01-27 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical probability and statistics are an attractive, thriving, and respectable part of mathematics. Some mathematicians and philosophers of science say they are the gateway to mathematics’ deepest mysteries. Moreover, mathematical statistics denotes an accumulation of mathematical discussions connected with efforts to most efficiently collect and use numerical data subject to random or deterministic variations. Currently, the concept of probability and mathematical statistics has become one of the fundamental notions of modern science and the philosophy of nature. This book is an illustration of the use of mathematics to solve specific problems in engineering, statistics, and science in general.
Download or read book Exploring Monte Carlo Methods written by William L. Dunn and published by Elsevier. This book was released on 2022-06-07 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring Monte Carlo Methods, Second Edition provides a valuable introduction to the numerical methods that have come to be known as "Monte Carlo." This unique and trusted resource for course use, as well as researcher reference, offers accessible coverage, clear explanations and helpful examples throughout. Building from the basics, the text also includes applications in a variety of fields, such as physics, nuclear engineering, finance and investment, medical modeling and prediction, archaeology, geology and transportation planning. Provides a comprehensive yet concise treatment of Monte Carlo methods Uses the famous "Buffon’s needle problem" as a unifying theme to illustrate the many aspects of Monte Carlo methods Includes numerous exercises and useful appendices on: Certain mathematical functions, Bose Einstein functions, Fermi Dirac functions and Watson functions
Download or read book A Guide to Monte Carlo Simulations in Statistical Physics written by David P. Landau and published by Cambridge University Press. This book was released on 2000-08-17 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, as well as in related fields, such as polymer science and lattice gauge theory. The authors give a succinct overview of simple sampling methods and develop the importance sampling method. In addition they introduce quantum Monte Carlo methods, aspects of simulations of growth phenomena and other systems far from equilibrium, and the Monte Carlo Renormalization Group approach to critical phenomena. The book includes many applications, examples, and current references, and exercises to help the reader.
Download or read book Monte Carlo Frameworks written by Daniel J. Duffy and published by John Wiley & Sons. This book was released on 2009-11-02 with total page 777 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is one of the first books that describe all the steps that are needed in order to analyze, design and implement Monte Carlo applications. It discusses the financial theory as well as the mathematical and numerical background that is needed to write flexible and efficient C++ code using state-of-the art design and system patterns, object-oriented and generic programming models in combination with standard libraries and tools. Includes a CD containing the source code for all examples. It is strongly advised that you experiment with the code by compiling it and extending it to suit your needs. Support is offered via a user forum on www.datasimfinancial.com where you can post queries and communicate with other purchasers of the book. This book is for those professionals who design and develop models in computational finance. This book assumes that you have a working knowledge of C ++.
Download or read book Monte Carlo Methods written by Malvin H. Kalos and published by John Wiley & Sons. This book was released on 2008-10-20 with total page 224 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 Schrodinger 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 Monte Carlo Methods written by Adrian Barbu and published by Springer Nature. This book was released on 2020-02-24 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book seeks to bridge the gap between statistics and computer science. It provides an overview of Monte Carlo methods, including Sequential Monte Carlo, Markov Chain Monte Carlo, Metropolis-Hastings, Gibbs Sampler, Cluster Sampling, Data Driven MCMC, Stochastic Gradient descent, Langevin Monte Carlo, Hamiltonian Monte Carlo, and energy landscape mapping. Due to its comprehensive nature, the book is suitable for developing and teaching graduate courses on Monte Carlo methods. To facilitate learning, each chapter includes several representative application examples from various fields. The book pursues two main goals: (1) It introduces researchers to applying Monte Carlo methods to broader problems in areas such as Computer Vision, Computer Graphics, Machine Learning, Robotics, Artificial Intelligence, etc.; and (2) it makes it easier for scientists and engineers working in these areas to employ Monte Carlo methods to enhance their research.
Download or read book Introducing Monte Carlo Methods with R written by Christian Robert and published by Springer Science & Business Media. This book was released on 2010 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Monte Carlo Method written by Yu.A. Shreider and published by Elsevier. This book was released on 2014-05-16 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications. Some of these applications include the computation of definite integrals, neutron physics, and in the investigation of servicing processes. This volume is comprised of seven chapters and begins with an overview of the basic features of the Monte Carlo method and typical examples of its application to simple problems in computational mathematics. The next chapter examines the computation of multi-dimensional integrals using the Monte Carlo method. Some examples of statistical modeling of integrals are analyzed, together with the accuracy of the computations. Subsequent chapters focus on the applications of the Monte Carlo method in neutron physics; in the investigation of servicing processes; in communication theory; and in the generation of uniformly distributed random numbers on electronic computers. Methods for organizing statistical experiments on universal digital computers are discussed. This book is designed for a wide circle of readers, ranging from those who are interested in the fundamental applications of the Monte Carlo method, to those who are concerned with comparatively limited problems of the peculiarities of simulating physical processes.
Download or read book Applications of Monte Carlo Methods in Biology Medicine and Other Fields of Science written by Charles J. Mode and published by BoD – Books on Demand. This book was released on 2011-02-28 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is an eclectic mix of applications of Monte Carlo methods in many fields of research should not be surprising, because of the ubiquitous use of these methods in many fields of human endeavor. In an attempt to focus attention on a manageable set of applications, the main thrust of this book is to emphasize applications of Monte Carlo simulation methods in biology and medicine.
Download or read book Monte Carlo Methods and Models in Finance and Insurance written by Ralf Korn and published by CRC Press. This book was released on 2010-02-26 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Rom
Download or read book Monte Carlo Methods and Codes for Nuclear Engineering Analysis written by Christopher Perfetti and published by Woodhead Publishing. This book was released on 2019-06-15 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo Methods and Codes for Nuclear Engineering Analysis provides a comprehensive survey of the state-of-the-art in radiation transport methods used by Monte Carlo (MC) codes. It then goes on to explore the real-world implementation of these methods in codes used by nuclear and scientists engineers, considering the advantages and disadvantages of the various techniques, design philosophies, and algorithm implementations. After a foreword and introduction giving a brief history of Monte Carlo methods, code systems, and their applications in nuclear science and engineering, subsequent chapters describe the fundamentals of Monte Carlo radiation transport methods by dividing the field into a number of topics or focus areas. The subjects selected include potential geometry and particle tracking, nuclear data, variance reduction, time-dependent analysis and parallel computing. Each chapter presents a comprehensive survey of the state-of-the-art implementations, algorithms, and methodologies used by production-level Monte Carlo codes for the area. A concluding chapter provides a handy summary by briefly listing the methods used by key Monte Carlo codes for each focus area in several tables. This book is an essential guide to Monte Carlo methods and codes for nuclear scientists, engineers and code developers in academia and industry and students studying this topic. discusses and compares the radiation transport methods in real-life Monte Carlo (MC) codes used by nuclear scientists and engineers presents in one convenient volume information previously scattered between conference papers, journal articles, and code manuals, thus allowing MC code users to compare the features and make and educated selections of the codes best meeting their needs chapters begin at a level that is appropriate for readers who are unfamiliar with the field, then go on to address the state-of-the-art
