Denoising Monte Carlo sensitivity estimates

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Monte Carlo methods are in widespread use both in academia and industry. We are, in particular, interested in improving sensitivity estimates obtained from Monte Carlo experiments with respect to given parameter values, motivated by, but not restricted to, financial applications. Denoising and interpolation methods, which have been used for a long time in many different areas, are proposed in a new form which is quadratic, easy to implement, and tailored to our objectives. This heuristic approach is supported by numerical experiments. (C) 2012 Elsevier B.V. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2012-05
Language
English
Article Type
Article
Citation

OPERATIONS RESEARCH LETTERS, v.40, no.3, pp.195 - 202

ISSN
0167-6377
DOI
10.1016/j.orl.2012.01.006
URI
http://hdl.handle.net/10203/101720
Appears in Collection
MA-Journal Papers(저널논문)IE-Journal Papers(저널논문)
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