On the optimization of Monte-Carlo simulations

Jaan Kalda

Physica A: Statistical Mechanics and its Applications, 1997, vol. 246, issue 3, 646-658

Abstract: The optimal planning of Monte-Carlo simulations is studied. It is assumed that (i) the aim of the simulations is to calculate the value of a certain parameter of a model function as accurately as possible; (ii) the simulations are performed at different values of the control parameter L; (iii) the parameters of the model function are calculated by the means of least-square fit. It is shown that the standard deviation of the outcome achieves minimum when the number of test points (i.e. different values of the parameter L used in simulations) equals the number n of unknown parameters in the model function.

Date: 1997
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437197003543
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

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:eee:phsmap:v:246:y:1997:i:3:p:646-658

DOI: 10.1016/S0378-4371(97)00354-3

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().