Optimal U—Type Designs

Peter Winker, Kai Tai Fang

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review


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.
Original languageEnglish
Title of host publicationMonte Carlo and Quasi-Monte Carlo Methods 1996
Subtitle of host publicationProceedings of a Conference at the University of Salzburg, Austria, July 9-12, 1996
EditorsHarald Niederreiter, Peter Hellekalek, Gerhard Larcher, Peter Zinterhof
PublisherSpringer New York
Number of pages13
ISBN (Electronic)9781461216902
ISBN (Print)9780387983356
Publication statusPublished - 14 Nov 1997
Externally publishedYes

Publication series

NameLecture Notes in Statistics
ISSN (Print)0930-0325
ISSN (Electronic)2197-7186


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