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Stochastic Simulation : algorithms and analysis
Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying...
| Auteurs principaux : | , |
|---|---|
| Format : | Livre |
| Langue : | anglais |
| Titre complet : | Stochastic Simulation : algorithms and analysis / Søren Asmussen, Peter W. Glynn. |
| Publié : |
New York, NY :
Springer New York
, [20..] Cham : Springer e-books Springer Nature |
| Collection : | Stochastic modelling and applied probability (Internet) ; 57 |
| Accès en ligne : |
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| Note sur l'URL : | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex |
| Condition d'utilisation et de reproduction : | Conditions particulières de réutilisation pour les bénéficiaires des licences nationales : https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |
| Sujets : | |
| Documents associés : | Autre format:
Stochastic simulation |
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| 225 | 2 | |a Stochastic Modelling and Applied Probability |v 57 | |
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| 330 | |a Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focuses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value. Søren Asmussen is a professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is the Thomas Ford professor of Engineering at Stanford University | ||
| 359 | 2 | |b 4, What This Book Is About |c An illustrative example : the single-served queue |c The Monte Carlo method |c Second example : option pricing |c Issues arising in the Monte Carlo context |c Further examples |c Introductory exercises |b 5, General Methods and Algorithms |c Generating Random Objects |c Output Analysis |c Steady-State Simulation |c Variance-Reduction Methods |c Rare-Event Simulation |c Derivative Estimation |c Stochastic Optimization |b 6, Algorithms for Special Models |c Numerical Integration |c Stochastic Differential Equations |c Gaussian Processes |c Lèvy Processes |c Markov Chain Monte Carlo Methods |c Selected Topics and Extended Examples | |
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