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SUMMARY:One D-optimal main effects design is not the other
DTSTART:20220627T124000Z
DTEND:20220627T130000Z
DTSTAMP:20240224T221400Z
UID:indico-contribution-259@conferences.enbis.org
DESCRIPTION:Speakers: Mohammed Saif Ismail Hameed (KU Leuven)\, Jose Nunez
Ares (KU Leuven)\, Peter Goos (KU Leuven\, Universiteit Antwerpen)\n\nWhe
n the run size of an experiment is a multiple of four\, D-optimal designs
for a main effects model can be obtained by dropping the appropriate numbe
r of factor columns from a Hadamard matrix. Alternatively\, one can use a
two-level orthogonal array. It is well known that one orthogonal array is
not the other\, and this has led to a rich literature on the choice of the
best orthogonal arrays for screening experiments with a number of runs th
at is a multiple of four. In this presentation\, we explain that dropping
any row from an orthogonal array results in a D-optimal main effects desig
n for an experiment whose number of runs is one less that a multiple of fo
ur\, provided the number of factors studied is not too large. We also show
that the amount of aliasing between main effects and two-factor interacti
ons as well as the amount of aliasing among the two-factor interactions st
rongly depends on the orthogonal array chosen and on the row dropped. We w
ill illustrate our points by a complete study of all D-optimal designs th
at can be obtained by dropping a row from the complete set of orthogonal a
rrays with 12\, 16 and 20 runs.\n\nhttps://conferences.enbis.org/event/18/
contributions/259/
LOCATION:EL5
RELATED-TO:indico-event-18@conferences.enbis.org
URL:https://conferences.enbis.org/event/18/contributions/259/
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