Monte Carlo Simulation Based Statistical Modeling

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Monte-Carlo Simulation-Based Statistical Modeling

Ding-Geng (Din) Chen,John Dean Chen
Monte Carlo Simulation Based Statistical Modeling Book PDF

Author : Ding-Geng (Din) Chen,John Dean Chen
Publisher : Springer
Page : 430 pages
File Size : 53,5 Mb
Release : 2017-02-01
Category : Medical
ISBN : 9789811033070

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Monte-Carlo Simulation-Based Statistical Modeling by Ding-Geng (Din) Chen,John Dean Chen Pdf

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.

Markov Chain Monte Carlo Simulations and Their Statistical Analysis

Bernd A Berg
Markov Chain Monte Carlo Simulations and Their Statistical Analysis Book PDF

Author : Bernd A Berg
Publisher : World Scientific Publishing Company
Page : 380 pages
File Size : 51,8 Mb
Release : 2004-10-01
Category : Science
ISBN : 9789813106376

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Markov Chain Monte Carlo Simulations and Their Statistical Analysis by Bernd A Berg Pdf

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++.

The Monte Carlo Method

Yu.A. Shreider
The Monte Carlo Method Book PDF

Author : Yu.A. Shreider
Publisher : Elsevier
Page : 394 pages
File Size : 55,6 Mb
Release : 2014-05-16
Category : Mathematics
ISBN : 9781483155579

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The Monte Carlo Method by Yu.A. Shreider Pdf

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.

Essentials of Monte Carlo Simulation

Nick T. Thomopoulos
Essentials of Monte Carlo Simulation Book PDF

Author : Nick T. Thomopoulos
Publisher : Springer Science & Business Media
Page : 184 pages
File Size : 44,5 Mb
Release : 2012-12-19
Category : Mathematics
ISBN : 9781461460220

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Essentials of Monte Carlo Simulation by Nick T. Thomopoulos Pdf

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.

Monte Carlo Simulation in Statistical Physics

Kurt Binder,Dieter W. Heermann
Monte Carlo Simulation in Statistical Physics Book PDF

Author : Kurt Binder,Dieter W. Heermann
Publisher : Springer Science & Business Media
Page : 202 pages
File Size : 46,8 Mb
Release : 2010-08-17
Category : Science
ISBN : 9783642031632

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Monte Carlo Simulation in Statistical Physics by Kurt Binder,Dieter W. Heermann Pdf

Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methodsand gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was the winner of the Berni J. Alder CECAM Award for Computational Physics 2001 as well as the Boltzmann Medal in 2007.

Vorticity, Statistical Mechanics, and Monte Carlo Simulation

Chjan Lim,Joseph Nebus
Vorticity Statistical Mechanics and Monte Carlo Simulation Book PDF

Author : Chjan Lim,Joseph Nebus
Publisher : Springer Science & Business Media
Page : 290 pages
File Size : 48,5 Mb
Release : 2007-07-28
Category : Mathematics
ISBN : 9780387494319

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Vorticity, Statistical Mechanics, and Monte Carlo Simulation by Chjan Lim,Joseph Nebus Pdf

This book is drawn from across many active fields of mathematics and physics. It has connections to atmospheric dynamics, spherical codes, graph theory, constrained optimization problems, Markov Chains, and Monte Carlo methods. It addresses how to access interesting, original, and publishable research in statistical modeling of large-scale flows and several related fields. The authors explicitly reach around the major branches of mathematics and physics, showing how the use of a few straightforward approaches can create a cornucopia of intriguing questions and the tools to answer them.

Markov Chain Monte Carlo Simulations and Their Statistical Analysis

Bernd A. Berg
Markov Chain Monte Carlo Simulations and Their Statistical Analysis Book PDF

Author : Bernd A. Berg
Publisher : World Scientific
Page : 380 pages
File Size : 55,5 Mb
Release : 2004
Category : Science
ISBN : 9789812389350

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Markov Chain Monte Carlo Simulations and Their Statistical Analysis by Bernd A. Berg Pdf

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++.

Monte Carlo Simulation in Statistical Physics

Kurt Binder,Dieter W. Heermann
Monte Carlo Simulation in Statistical Physics Book PDF

Author : Kurt Binder,Dieter W. Heermann
Publisher : Springer Science & Business Media
Page : 132 pages
File Size : 49,5 Mb
Release : 2013-11-11
Category : Science
ISBN : 9783662302736

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Monte Carlo Simulation in Statistical Physics by Kurt Binder,Dieter W. Heermann Pdf

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.

A Guide to Monte Carlo Simulations in Statistical Physics

David P. Landau,Kurt Binder
A Guide to Monte Carlo Simulations in Statistical Physics Book PDF

Author : David P. Landau,Kurt Binder
Publisher : Cambridge University Press
Page : 456 pages
File Size : 45,6 Mb
Release : 2005-09
Category : Computers
ISBN : 0521842387

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A Guide to Monte Carlo Simulations in Statistical Physics by David P. Landau,Kurt Binder Pdf

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 Statistical Methods

Christian Robert,George Casella
Monte Carlo Statistical Methods Book PDF

Author : Christian Robert,George Casella
Publisher : Springer Science & Business Media
Page : 522 pages
File Size : 53,8 Mb
Release : 2013-03-14
Category : Mathematics
ISBN : 9781475730715

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Monte Carlo Statistical Methods by Christian Robert,George Casella Pdf

We have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments.

Monte Carlo Methods and Models in Finance and Insurance

Ralf Korn,Elke Korn,Gerald Kroisandt
Monte Carlo Methods and Models in Finance and Insurance Book PDF

Author : Ralf Korn,Elke Korn,Gerald Kroisandt
Publisher : CRC Press
Page : 485 pages
File Size : 45,7 Mb
Release : 2010-02-26
Category : Business & Economics
ISBN : 9781420076196

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Monte Carlo Methods and Models in Finance and Insurance by Ralf Korn,Elke Korn,Gerald Kroisandt Pdf

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

Monte Carlo Simulation and Resampling Methods for Social Science

Thomas M. Carsey,Jeffrey J. Harden
Monte Carlo Simulation and Resampling Methods for Social Science Book PDF

Author : Thomas M. Carsey,Jeffrey J. Harden
Publisher : SAGE Publications
Page : 304 pages
File Size : 53,6 Mb
Release : 2013-08-05
Category : Social Science
ISBN : 9781483324920

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Monte Carlo Simulation and Resampling Methods for Social Science by Thomas M. Carsey,Jeffrey J. Harden Pdf

Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and Jeffrey J. Harden, 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.

Modeling and Simulation Fundamentals

John A. Sokolowski,Catherine M. Banks
Modeling and Simulation Fundamentals Book PDF

Author : John A. Sokolowski,Catherine M. Banks
Publisher : John Wiley & Sons
Page : 468 pages
File Size : 46,7 Mb
Release : 2010-04-19
Category : Mathematics
ISBN : 9780470486740

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Modeling and Simulation Fundamentals by John A. Sokolowski,Catherine M. Banks Pdf

An insightful presentation of the key concepts, paradigms, and applications of modeling and simulation Modeling and simulation has become an integral part of research and development across many fields of study, having evolved from a tool to a discipline in less than two decades. Modeling and Simulation Fundamentals offers a comprehensive and authoritative treatment of the topic and includes definitions, paradigms, and applications to equip readers with the skills needed to work successfully as developers and users of modeling and simulation. Featuring contributions written by leading experts in the field, the book's fluid presentation builds from topic to topic and provides the foundation and theoretical underpinnings of modeling and simulation. First, an introduction to the topic is presented, including related terminology, examples of model development, and various domains of modeling and simulation. Subsequent chapters develop the necessary mathematical background needed to understand modeling and simulation topics, model types, and the importance of visualization. In addition, Monte Carlo simulation, continuous simulation, and discrete event simulation are thoroughly discussed, all of which are significant to a complete understanding of modeling and simulation. The book also features chapters that outline sophisticated methodologies, verification and validation, and the importance of interoperability. A related FTP site features color representations of the book's numerous figures. Modeling and Simulation Fundamentals encompasses a comprehensive study of the discipline and is an excellent book for modeling and simulation courses at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners in the fields of computational statistics, engineering, and computer science who use statistical modeling techniques.

An Introduction to Statistical Computing

Jochen Voss
An Introduction to Statistical Computing Book PDF

Author : Jochen Voss
Publisher : John Wiley & Sons
Page : 322 pages
File Size : 46,9 Mb
Release : 2013-08-28
Category : Mathematics
ISBN : 9781118728024

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An Introduction to Statistical Computing by Jochen Voss Pdf

A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R. This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course.

Modeling and Simulation Fundamentals

John A. Sokolowski,Catherine M. Banks
Modeling and Simulation Fundamentals Book PDF

Author : John A. Sokolowski,Catherine M. Banks
Publisher : John Wiley & Sons
Page : 453 pages
File Size : 41,9 Mb
Release : 2010-07-13
Category : Mathematics
ISBN : 9780470590614

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Modeling and Simulation Fundamentals by John A. Sokolowski,Catherine M. Banks Pdf

An insightful presentation of the key concepts, paradigms, and applications of modeling and simulation Modeling and simulation has become an integral part of research and development across many fields of study, having evolved from a tool to a discipline in less than two decades. Modeling and Simulation Fundamentals offers a comprehensive and authoritative treatment of the topic and includes definitions, paradigms, and applications to equip readers with the skills needed to work successfully as developers and users of modeling and simulation. Featuring contributions written by leading experts in the field, the book's fluid presentation builds from topic to topic and provides the foundation and theoretical underpinnings of modeling and simulation. First, an introduction to the topic is presented, including related terminology, examples of model development, and various domains of modeling and simulation. Subsequent chapters develop the necessary mathematical background needed to understand modeling and simulation topics, model types, and the importance of visualization. In addition, Monte Carlo simulation, continuous simulation, and discrete event simulation are thoroughly discussed, all of which are significant to a complete understanding of modeling and simulation. The book also features chapters that outline sophisticated methodologies, verification and validation, and the importance of interoperability. A related FTP site features color representations of the book's numerous figures. Modeling and Simulation Fundamentals encompasses a comprehensive study of the discipline and is an excellent book for modeling and simulation courses at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners in the fields of computational statistics, engineering, and computer science who use statistical modeling techniques.