Variance reduction methods for simulation of densities on Wiener space
Contribuinte(s) |
Universitat Pompeu Fabra. Departament d'Economia i Empresa |
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Data(s) |
15/09/2005
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Resumo |
We develop a general error analysis framework for the Monte Carlo simulationof densities for functionals in Wiener space. We also study variancereduction methods with the help of Malliavin derivatives. For this, wegive some general heuristic principles which are applied to diffusionprocesses. A comparison with kernel density estimates is made. |
Identificador | |
Idioma(s) |
eng |
Direitos |
L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons info:eu-repo/semantics/openAccess <a href="http://creativecommons.org/licenses/by-nc-nd/3.0/es/">http://creativecommons.org/licenses/by-nc-nd/3.0/es/</a> |
Palavras-Chave | #Statistics, Econometrics and Quantitative Methods #stochastic differential equations #weak approximation #variance reduction #kernel density estimation |
Tipo |
info:eu-repo/semantics/workingPaper |