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Monte-Carlo Methods and Stochastic Processes : From Linear to Non-Linear (Hardcover) (Emmanuel Gobet)
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The goal is to offer an introductory book on Monte-Carlo methods applied to stochastic processes, starting from the standard case and going to the most recent models, which will appeal to a wide audience. Computational and mathematical aspects will be discussed in detail, in order to make the book accessible to non-specialists and to introduce them to the most advanced convergence tools of these Monte-Carlo methods. Modern arguments from probability, statistics and machine learning will be included in order to justify the convergence of algorithms and numerical schemes. Exercises and code (or pseudo-code) will be included. Additional material will be placed on a web site.