Exploring Monte Carlo Methods - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Exploring Monte Carlo Methods write by William L. Dunn. This book was released on 2022-06-07. Exploring Monte Carlo Methods available in PDF, EPUB and Kindle. 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
Exploring Monte Carlo Methods
Exploring Monte Carlo Methods - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Exploring Monte Carlo Methods write by William L. Dunn. This book was released on 2011-04. Exploring Monte Carlo Methods available in PDF, EPUB and Kindle.
Monte Carlo Simulation and Resampling Methods for Social Science
Monte Carlo Simulation and Resampling Methods for Social Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Monte Carlo Simulation and Resampling Methods for Social Science write by Thomas M. Carsey. This book was released on 2013-08-05. Monte Carlo Simulation and Resampling Methods for Social Science available in PDF, EPUB and Kindle. 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.
Explorations in Monte Carlo Methods
Explorations in Monte Carlo Methods - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Explorations in Monte Carlo Methods write by Ronald W. Shonkwiler. This book was released on 2009-08-11. Explorations in Monte Carlo Methods available in PDF, EPUB and Kindle. Monte Carlo methods are among the most used and useful computational tools available today, providing efficient and practical algorithims to solve a wide range of scientific and engineering problems. Applications covered in this book include optimization, finance, statistical mechanics, birth and death processes, and gambling systems. Explorations in Monte Carlo Methods provides a hands-on approach to learning this subject. Each new idea is carefully motivated by a realistic problem, thus leading from questions to theory via examples and numerical simulations. Programming exercises are integrated throughout the text as the primary vehicle for learning the material. Each chapter ends with a large collection of problems illustrating and directing the material. This book is suitable as a textbook for students of engineering and the sciences, as well as mathematics.
Handbook of Monte Carlo Methods
Handbook of Monte Carlo Methods - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of Monte Carlo Methods write by Dirk P. Kroese. This book was released on 2013-06-06. Handbook of Monte Carlo Methods available in PDF, EPUB and Kindle. 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.
