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...
Tallennettuna:
| Päätekijät: | , |
|---|---|
| Aineistotyyppi: | Livre numérique |
| Kieli: | Anglais |
| Julkaistu: |
New York, NY :
Springer New York : Springer e-books
[20..].
Cham : Springer Nature |
| Sarja: | Stochastic Modelling and Applied Probability
57 |
| Aiheet: | |
| Linkit: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Huomautus: |
L'impression du document génère 479 p. Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Stochastic simulation, algorithms and analysis, Søren Asmussen, Peter W. Glynn, 2007, New York, Springer, 1 vol. (XIV-476 p.), Stochastic modelling and applied probability, 978-0-387-30679-7 |
| LEADER | 04122nam a22004577a 4500 | ||
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| 001 | 938757 | ||
| 008 | 080410q2000 xxe ||| |||| 00| 0 eng d | ||
| 009 | PPN123144310 | ||
| 020 | |a 9780387690339 | ||
| 041 | 0 | |a eng | |
| 082 | |a 519.2 | ||
| 084 | |a 65C20. 2010 | ||
| 084 | |a 60G07. 2010 | ||
| 100 | 1 | |a Asmussen, Søren, |d 1946-...., |c mathématicien. | |
| 245 | 1 | 0 | |a Stochastic Simulation : |b algorithms and analysis |c Søren Asmussen, Peter W. Glynn. |
| 260 | |a New York, NY : |b Springer New York : |b Springer e-books. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 1 | |a Stochastic Modelling and Applied Probability |v 57 | |
| 500 | |a L'impression du document génère 479 p. | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 504 | |a Bibliogr. Index | ||
| 505 | 0 | |a 4, What This Book Is About -- 5, General Methods and Algorithms -- 6, Algorithms for Special Models -- An illustrative example : the single-served queue -- The Monte Carlo method -- Second example : option pricing -- Issues arising in the Monte Carlo context -- Further examples -- Introductory exercises -- Generating Random Objects -- Output Analysis -- Steady-State Simulation -- Variance-Reduction Methods -- Rare-Event Simulation -- Derivative Estimation -- Stochastic Optimization -- Numerical Integration -- Stochastic Differential Equations -- Gaussian Processes -- Lèvy Processes -- Markov Chain Monte Carlo Methods -- Selected Topics and Extended Examples | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |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 | ||
| 650 | |a Markov, processus de | ||
| 650 | |a Méthode de Monte-Carlo | ||
| 650 | |a Équations différentielles stochastiques | ||
| 650 | |a Analyse stochastique | ||
| 650 | |a Processus de Lévy | ||
| 650 | |a Processus gaussiens | ||
| 650 | |a Simulation, méthodes de | ||
| 700 | 1 | |a Glynn, Peter W. |4 aut | |
| 776 | 0 | |0 117579556 |t Stochastic simulation |o algorithms and analysis |f Søren Asmussen, Peter W. Glynn |d 2007 |c New York |n Springer |p 1 vol. (XIV-476 p.) |s Stochastic modelling and applied probability |z 978-0-387-30679-7 | |
| 856 | 4 | |q PDF |u https://doi.org/10.1007/978-0-387-69033-9 |z Accès sur la plateforme de l'éditeur | |
| 856 | 4 | |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-9MJCLF45-K |z Accès sur la plateforme Istex | |
| 856 | 4 | |5 452349901:747889988 |u https://ezproxy.univ-orleans.fr/login?url=https://doi.org/10.1007/978-0-387-69033-9 |z Accès Université d'Orléans | |
| 856 | 4 | |5 180339901:750903104 |u https://ezproxy.insa-cvl.fr/login?qurl=https://doi.org/10.1007/978-0-387-69033-9 |z Accès INSA CVL | |
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