Mathematical Foundations of Stochastic Simulation
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Köp båda 2 för 865 krCarl Graham is a CNRS researcher and Professeur charg de cours (part-time associate professor) at the cole Polytechnique and associate editor for Annals of Applied Probability. His main fields of research include stochastic processes, stochastic modelling and communication networks. Denis Talay is a senior researcher at Inria. He holds a part time research position at cole Polytechnique where he had taught for 13 years. He is, or has been, an associate editor for many top journals in probability, numerical analysis, financial mathematics and scientific computing. He was the president of the French Applied Math. Society SMAI (2006-2009) and is now the Chair of its Scientific Council. His main fields of interest are stochastic modelling, numerical probability, stochastic analysis of partial differential equations and financial mathematics.
Part I:Principles of Monte Carlo Methods.- 1.Introduction.- 2.Strong Law of Large Numbers and Monte Carlo Methods.- 3.Non Asymptotic Error Estimates for Monte Carlo Methods.- Part II:Exact and Approximate Simulation of Markov Processes.- 4.Poisson Processes.- 5.Discrete-Space Markov Processes.- 6.Continuous-Space Markov Processes with Jumps.- 7.Discretization of Stochastic Differential Equations.- Part III:Variance Reduction, Girsanovs Theorem, and Stochastic Algorithms.- 8.Variance Reduction and Stochastic Differential Equations.- 9.Stochastic Algorithms.- References.- Index.