Stochastic Simulation: Algorithms and Analysis
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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; the second half discusses model-specific algorithms. Exercises and illustrations are included.
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- Autor: Peter W. Glynn / Søren Asmussen
- Seitenzahl: 482
- Format: PDF
- DRM: social-drm (ohne Kopierschutz)
- Erscheinungsdatum: 14.07.2007
- Herausgeber: SPRINGER