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Monte Carlo method

  • Handbook of Markov Chain Monte Carloby Steve Brooks; Andrew Gelman; Galin Jones; Xiao-Li Meng

    Taylor and Francis 2011; US$ 109.95

    Since their popularization in the 1990s, Markov chain Monte Carlo (MCMC) methods have revolutionized statistical computing and have had an especially profound impact on the practice of Bayesian statistics. Furthermore, MCMC methods have enabled the development and use of intricate models in an astonishing array of disciplines as diverse as fisheries... more...

  • Sequential Monte Carlo Methods for Nonlinear Discrete-Time Filteringby Marcelo G. S. Bruno

    Morgan & Claypool Publishers 2013; US$ 40.00

    In these notes, we introduce particle filtering as a recursive importance sampling method that approximates the minimum-mean-square-error (MMSE) estimate of a sequence of hidden state vectors in scenarios where the joint probability distribution of the states and the observations is non-Gaussian and, therefore, closed-form analytical expressions for... more...

  • Simulation and Monte Carloby J. S. Dagpunar

    Wiley 2007; US$ 153.00

    Simulation and Monte Carlo is aimed at students studying for degrees in Mathematics, Statistics, Financial Mathematics, Operational Research, Computer Science, and allied subjects, who wish an up-to-date account of the theory and practice of Simulation. Its distinguishing features are in-depth accounts of the theory of Simulation, including the important... more...

  • Mean Field Simulation for Monte Carlo Integrationby Pierre Del Moral

    Taylor and Francis 2013; US$ 99.95

    In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle... more...

  • Premiers pas en simulation (Statistique et probabilités appliquées) (French Edition)by Yadolah Dodge; Giuseppe Melfi

    Springer 2008; US$ 29.95

    Ce livre est une introduction aux techniques de simulation. Après un bref rappel des techniques fondamentales du calcul des probabilités, il expose divers procédés pour générer en grande quantités des nombres aléatoires. Les transformations de variables utilisées pour simuler des échantillons fictifs d?une variable aléatoire et les tests d?hypothèses... more...

  • Exploring Monte Carlo Methodsby William L. Dunn; J. Kenneth Shultis

    Elsevier Science 2011; US$ 124.00

    Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which... more...

  • Statistical Simulationby Todd C. Headrick

    Taylor and Francis 2010; US$ 104.95

    Although power method polynomials based on the standard normal distributions have been used in many different contexts for the past 30 years, it was not until recently that the probability density function (pdf) and cumulative distribution function (cdf) were derived and made available. Focusing on both univariate and multivariate nonnormal data generation,... more...

  • Monte Carlo Methodsby Malvin H. Kalos; Paula A. Whitlock

    Wiley 2008; US$ 170.00

    This introduction to Monte Carlo Methods seeks to identify and study the unifying elements that underlie their effective application. It 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... more...

  • Monte Carlo and Quasi-Monte Carlo Samplingby Christiane Lemieux

    Springer 2009; US$ 119.00

    Presents essential tools for using quasi-Monte Carlo sampling in practice. This book focuses on issues related to Monte Carlo methods - uniform and non-uniform random number generation, variance reduction techniques. It covers several aspects of quasi-Monte Carlo methods. more...

  • Minimization of Computational Costs of Non-Analogue Monte Carlo Methodsby Gennadii A. Mikhailov

    World Scientific Publishing Company 1992; US$ 92.00

    Non-analogue Monte Carlo methods are useful when the direct simulation techniques are insufficient. To use the additional discretization, Monte Carlo estimates are biased and it is desirable to optimize the connection between discretization parameters and the sample size. In this connection, the book investigates variances of non-analogue Monte Carlo... more...