{"product_id":"mcm-handbook-9780470177938","title":"MCM Handbook","description":"\u003cb\u003eA comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications\u003c\/b\u003e \u003cp\u003eMore 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. \u003ci\u003eHandbook of Monte Carlo Methods\u003c\/i\u003e provides the theory, algorithms, and applications that helps provide a thorough understanding of the emerging dynamics of this rapidly-growing field.\u003c\/p\u003e \u003cp\u003eThe 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: \u003c\/p\u003e \u003cul\u003e \u003cli\u003eRandom variable and stochastic process generation\u003c\/li\u003e \u003cli\u003eMarkov chain Monte Carlo, featuring key algorithms such as the Metropolis-Hastings method, the Gibbs sampler, and hit-and-run\u003c\/li\u003e \u003cli\u003eDiscrete-event simulation\u003c\/li\u003e \u003cli\u003eTechniques for the statistical analysis of simulation data including the delta method, steady-state estimation, and kernel density estimation\u003c\/li\u003e \u003cli\u003eVariance reduction, including importance sampling, latin hypercube sampling, and conditional Monte Carlo\u003c\/li\u003e \u003cli\u003eEstimation of derivatives and sensitivity analysis\u003c\/li\u003e \u003cli\u003eAdvanced topics including cross-entropy, rare events, kernel density estimation, quasi Monte Carlo, particle systems, and randomized optimization\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThe presented theoretical concepts are illustrated with worked examples that use MATLAB\u003csup\u003e(R)\u003c\/sup\u003e, a related Web site houses the MATLAB\u003csup\u003e(R)\u003c\/sup\u003e 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.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eHandbook of Monte Carlo Methods\u003c\/i\u003e 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.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Dirk P. Kroese, Thomas Taimre, Zdravko I. Botev\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Wiley\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 03\/15\/2011\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 772\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Hardcover\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 3.35lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 10.00h x 7.10w x 1.70d\u003cbr\u003e\u003cb\u003eISBN:\u003c\/b\u003e 9780470177938\u003cbr\u003e\u003cbr\u003e\u003cb\u003eReview Citation(s): \u003c\/b\u003e\u003cbr\u003e\u003ci\u003eReference and Research Bk News\u003c\/i\u003e 06\/01\/2011 pg. 211\u003cbr\u003e\u003cp\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eDirk P. Kroese, PhD, \u003c\/b\u003e is Australian Professorial Fellow in Statistics at The University of Queensland (Australia). Dr. Kroese has more than seventy publications in such areas as stochastic modeling, randomized algorithms, computational statistics, and reliability. He is a pioneer of the cross-entropy method and the coauthor of Simulation and the Monte Carlo Method, Second Edition (Wiley). \u003c\/p\u003e\u003cp\u003e\u003cb\u003eThomas Taimre, PhD, \u003c\/b\u003e is a Postdoctoral Research Fellow at The University of Queensland. He currently focuses his research on Monte Carlo methods and simulation, from the theoretical foundations to performing computer implementations.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e Zdravko I. Botev, PhD\u003c\/b\u003e, is a Postdoctoral Research Fellow at the University of Montreal (Canada). His research interests include the splitting method for rare-event simulation and kernel density estimation. He is the author of one of the most widely used free MATLAB(R) statistical software programs for nonparametric kernel density estimation.\u003c\/p\u003e\u003cbr\u003e\u003cp\u003e\u003ci\u003eThis title is not returnable\u003c\/i\u003e\u003cbr\u003e\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Hardcover","offer_id":40189623861363,"sku":"9.78047E+12","price":184.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0555\/9255\/0515\/products\/img_44c23fcf-4644-4f6e-8cf8-6210215e7d51.jpg?v=1655817676","url":"https:\/\/bookstorenmore.com\/products\/mcm-handbook-9780470177938","provider":"Bookstore N More","version":"1.0","type":"link"}