Monte Carlo Simulation Based Statistical Modeling
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Monte Carlo Simulation Based Statistical Modeling
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Author : Ding-Geng (Din) Chen
language : en
Publisher: Springer
Release Date : 2017-02-01
Monte Carlo Simulation Based Statistical Modeling written by Ding-Geng (Din) Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-01 with Medical categories.
This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.
Monte Carlo Simulation And Resampling Methods For Social Science
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Author : Thomas M. Carsey
language : en
Publisher: SAGE Publications
Release Date : 2013-08-05
Monte Carlo Simulation And Resampling Methods For Social Science written by Thomas M. Carsey and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-05 with Social Science categories.
Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, this book examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.
Monte Carlo Simulation In Statistical Physics
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Author : Kurt Binder
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Monte Carlo Simulation In Statistical Physics written by Kurt Binder 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 2013-11-11 with Science categories.
When learning very formal material one comes to a stage where one thinks one has understood the material. Confronted with a "realiife" problem, the passivity of this understanding sometimes becomes painfully elear. To be able to solve the problem, ideas, methods, etc. need to be ready at hand. They must be mastered (become active knowledge) in order to employ them successfully. Starting from this idea, the leitmotif, or aim, of this book has been to elose this gap as much as possible. How can this be done? The material presented here was born out of a series of lectures at the Summer School held at Figueira da Foz (Portugal) in 1987. The series of lectures was split into two concurrent parts. In one part the "formal material" was presented. Since the background of those attending varied widely, the presentation of the formal material was kept as pedagogic as possible. In the formal part the general ideas behind the Monte Carlo method were developed. The Monte Carlo method has now found widespread appli cation in many branches of science such as physics, chemistry, and biology. Because of this, the scope of the lectures had to be narrowed down. We could not give a complete account and restricted the treatment to the ap plication of the Monte Carlo method to the physics of phase transitions. Here particular emphasis is placed on finite-size effects.
Essentials Of Monte Carlo Simulation
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Author : Nick T. Thomopoulos
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-19
Essentials Of Monte Carlo Simulation written by Nick T. Thomopoulos 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 2012-12-19 with Mathematics categories.
Essentials of Monte Carlo Simulation focuses on the fundamentals of Monte Carlo methods using basic computer simulation techniques. The theories presented in this text deal with systems that are too complex to solve analytically. As a result, readers are given a system of interest and constructs using computer code, as well as algorithmic models to emulate how the system works internally. After the models are run several times, in a random sample way, the data for each output variable(s) of interest is analyzed by ordinary statistical methods. This book features 11 comprehensive chapters, and discusses such key topics as random number generators, multivariate random variates, and continuous random variates. Over 100 numerical examples are presented as part of the appendix to illustrate useful real world applications. The text also contains an easy to read presentation with minimal use of difficult mathematical concepts. Very little has been published in the area of computer Monte Carlo simulation methods, and this book will appeal to students and researchers in the fields of Mathematics and Statistics.
Markov Chain Monte Carlo Simulations And Their Statistical Analysis With Web Based Fortran Code
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Author : Bernd Albert Berg
language : en
Publisher: World Scientific Publishing Company
Release Date : 2004-10-01
Markov Chain Monte Carlo Simulations And Their Statistical Analysis With Web Based Fortran Code written by Bernd Albert Berg and has been published by World Scientific Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-10-01 with Science categories.
This book teaches modern Markov chain Monte Carlo (MC) simulation techniques step by step. The material should be accessible to advanced undergraduate students and is suitable for a course. It ranges from elementary statistics concepts (the theory behind MC simulations), through conventional Metropolis and heat bath algorithms, autocorrelations and the analysis of the performance of MC algorithms, to advanced topics including the multicanonical approach, cluster algorithms and parallel computing. Therefore, it is also of interest to researchers in the field. The book relates the theory directly to Web-based computer code. This allows readers to get quickly started with their own simulations and to verify many numerical examples easily. The present code is in Fortran 77, for which compilers are freely available. The principles taught are important for users of other programming languages, like C or C++.
Random Number Generation And Monte Carlo Methods
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Author : James E. Gentle
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-18
Random Number Generation And Monte Carlo Methods written by James E. Gentle 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 2006-04-18 with Computers categories.
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.
A Guide To Monte Carlo Simulations In Statistical Physics
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Author : David P. Landau
language : en
Publisher: Cambridge University Press
Release Date : 2005-09
A Guide To Monte Carlo Simulations In Statistical Physics written by David P. Landau and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-09 with Computers categories.
This updated edition deals with the Monte Carlo simulation of complex physical systems encountered in condensed-matter physics, statistical mechanics, and related fields. It contains many applications, examples, and exercises to help the reader. It is an excellent guide for graduate students and researchers who use computer simulations in their research.
Monte Carlo Simulation
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Author : Christopher Z. Mooney
language : en
Publisher: SAGE
Release Date : 1997-04-07
Monte Carlo Simulation written by Christopher Z. Mooney and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-04-07 with Mathematics categories.
Aimed at researchers across the social sciences, this book explains the logic behind the Monte Carlo simulation method and demonstrates its uses for social and behavioural research.
Statistical Modeling And Computation
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Author : Joshua C. C. Chan
language : en
Publisher: Springer Nature
Release Date : 2025-01-21
Statistical Modeling And Computation written by Joshua C. C. Chan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-21 with Computers categories.
This book, Statistical Modeling and Computation, provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of mathematical statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications. The 2nd edition changes the programming language used in the text from MATLAB to Julia. For all examples with computing components, the authors provide data sets and their own Julia codes. The new edition features numerous full color graphics to illustrate the concepts discussed in the text, and adds three entirely new chapters on a variety of popular topics, including: Regularization and the Lasso regression Bayesian shrinkage methods Nonparametric statistical tests Splines and the Gaussian process regression Joshua C. C. Chan is Professor of Economics, and holds the endowed Olson Chair at Purdue University. He is an elected fellow at the International Association for Applied Econometrics and served as Chair for the Economics, Finance and Business Section of the International Society for Bayesian Analysis from 2020-2022. His research focuses on building new high-dimensional time-series models and developing efficient estimation methods for these models. He has published over 50 papers in peer-reviewed journals, including some top-field journals such as Journal of Econometrics, Journal of the American Statistical Association and Journal of Business and Economic Statistics. Dirk Kroese is Professor of Mathematics and Statistics at the University of Queensland. He is known for his significant contributions to the fields of applied probability, mathematical statistics, machine learning, and Monte Carlo methods. He has published over 140 articles and 7 books. He is a pioneer of the well-known Cross-Entropy (CE) method, which is being used around the world to help solve difficult estimation and optimization problems in science, engineering, and finance. In addition to his scholarly contributions, Dirk Kroese is recognized for his role as an educator and mentor, having supervised and inspired numerous students and researchers.
Monte Carlo Simulation For The Pharmaceutical Industry
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Author : Mark Chang
language : en
Publisher: CRC Press
Release Date : 2010-09-29
Monte Carlo Simulation For The Pharmaceutical Industry written by Mark Chang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-29 with Mathematics categories.
Helping you become a creative, logical thinker and skillful "simulator," Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies provides broad coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization. It presents the theories and metho