Preliminary control variates to improve empirical regression methods
Ben Zineb Tarik () and
Gobet Emmanuel ()
Additional contact information
Ben Zineb Tarik: Centre de Mathématiques Appliquées, Ecole Polytechnique and CNRS, 91128 Palaiseau Cedex, France
Gobet Emmanuel: Centre de Mathématiques Appliquées, Ecole Polytechnique and CNRS, 91128 Palaiseau Cedex, France
Monte Carlo Methods and Applications, 2013, vol. 19, issue 4, 331-354
Abstract:
We design a variance reduction method to reduce the estimation error in regression problems. It is based on an appropriate use of other known regression functions. Theoretical estimates are supporting this improvement and numerical experiments are illustrating the efficiency of the method.
Keywords: Empirical regression; variance reduction; distribution-free theory (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://doi.org/10.1515/mcma-2013-0015 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bpj:mcmeap:v:19:y:2013:i:4:p:331-354:n:4
Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/mcma/html
DOI: 10.1515/mcma-2013-0015
Access Statistics for this article
Monte Carlo Methods and Applications is currently edited by Karl K. Sabelfeld
More articles in Monte Carlo Methods and Applications from De Gruyter
Bibliographic data for series maintained by Peter Golla ().