Skip navigation
User training | Reference and search service

Library catalog

Content aggregators
Please use this identifier to cite or link to this item:

Title: An efficient algorithm for accelerating Monte Carlo approximations of the solution to boundary value problems
Authors: Mancini, S.
Bernal, F.
Acebron, J. A.
Keywords: Bounded diffusion
Feynman–Kac formula
First exit time
Monte Carlo method
Parallel computing
Romberg extrapolation
Issue Date: 2016
Publisher: Springer/Plenum Publishers
Abstract: The numerical approximation of boundary value problems by means of a probabilistic representations often has the drawback that the Monte Carlo estimate of the solution is substantially biased due to the presence of the domain boundary. We introduce a scheme, which we have called the leading-term Monte Carlo regression, which seeks to remove that bias by replacing a ’cloud’ of Monte Carlo estimates—carried out at different discretization levels—for the usual single Monte Carlo estimate. The practical result of our scheme is an acceleration of the Monte Carlo method. Theoretical analysis of the proposed scheme, confirmed by numerical experiments, shows that the achieved speedup can be well over 100.
Peer reviewed: yes
DOI: 10.1007/s10915-015-0033-4
ISSN: 0885-7474
Accession number: WOS:000368733500006
Appears in Collections:CTI-RI - Artigos em revistas científicas internacionais com arbitragem científica

Files in This Item:
File Description SizeFormat 
JSciComput2016.pdfVersão Editora1.27 MBAdobe PDFView/Open    Request a copy

FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote Currículo DeGóis 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.