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...
Αποθηκεύτηκε σε:
| Κύριοι συγγραφείς: | , |
|---|---|
| Μορφή: | Livre numérique |
| Γλώσσα: | Anglais |
| Έκδοση: |
New York, NY :
Springer New York : Springer e-books
[20..].
Cham : Springer Nature |
| Σειρά: | Stochastic Modelling and Applied Probability
57 |
| Θέματα: | |
| Διαθέσιμο Online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Σημείωση: |
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 |
Πίνακας περιεχομένων:
- 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