Konferenzpaper

Erschienen in: Monte Carlo and Quasi-Monte Carlo Methods 1996

Herausgeberliste: Niederreiter, H.; Hellekalek, P.; Larcher, G.; Zinterhof, P.

Jahr der Veröffentlichung: 1998

Seiten: 436-448

ISBN: 978-0-387-98335-6

eISBN: 978-1-4612-1690-2

DOI Link: https://doi.org/10.1007/978-1-4612-1690-2_31

Konferenz: 2nd International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

Serientitel: Lecture notes in statistics

Serienzählung: 127

Abstract: 

Designs with low discrepancy are of interest in many areas of statistical work. U-type designs are among the most widely studied design classes. In this paper a heuristic global optimization algorithm, Threshold Accepting, is used to find optimal U-type designs (uniform designs) or at least good approximations to uniform designs. As the evaluation of the discrepancy of a given point set is performed by an exact algorithm, the application presented here is restricted to small numbers of experiments in low dimensional spaces. The comparison with known optimal results for the two-factor uniform design and good designs for three to five factors shows a good performance of the algorithm.

Harvard-Zitierstil: Winker, P. and Fang, K. (1998) Optimal U-Type Designs, in Niederreiter, H., Hellekalek, P., Larcher, G. and Zinterhof, P. (eds.) Monte Carlo and Quasi-Monte Carlo Methods 1996. New York: Springer . pp. 436-448. https://doi.org/10.1007/978-1-4612-1690-2_31

APA-Zitierstil: Winker, P., & Fang, K. (1998). Optimal U-Type Designs. In Niederreiter, H., Hellekalek, P., Larcher, G., & Zinterhof, P. (Eds.), Monte Carlo and Quasi-Monte Carlo Methods 1996. (pp. 436-448). Springer . https://doi.org/10.1007/978-1-4612-1690-2_31