Title page for etd-0728103-143737


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URN etd-0728103-143737
Author Chao-Jin Chou
Author's Email Address m9024621@student.nsysu.edu.tw
Statistics This thesis had been viewed 5067 times. Download 1656 times.
Department Applied Mathematics
Year 2002
Semester 2
Degree Master
Type of Document
Language English
Title Robust A-optimal designs for mixture experiments in Scheffe' models
Date of Defense 2003-06-06
Page Count 43
Keyword
  • equivalence theorem
  • invariant symmetric block matrices
  • robust design.
  • Convex combination
  • Abstract A mixture experiment is an
    experiments in which the q-ingredients are nonnegative
    and subject to the simplex restriction on
    the (q-1)-dimentional probability simplex. In this
    work , we investigate the robust A-optimal designs for mixture
    experiments with uncertainty on the linear, quadratic models
    considered by Scheffe' (1958). In Chan (2000), a review on the
    optimal designs including A-optimal designs are presented for
    each of the Scheffe's linear and quadratic models. We will use
    these results to find the robust A-optimal design for the linear
    and quadratic models under some robust A-criteria. It is shown
    with the two types of robust A-criteria defined here, there
    exists a convex combination of the individual A-optimal designs
    for linear and quadratic models respectively to be robust
    A-optimal. In the end, we compare efficiencies of these optimal
    designs with respect to different A-criteria.
    Advisory Committee
  • Fu-Chuen Chang - chair
  • Chwen-Ming Chang - co-chair
  • Grace Shwu-Rong Shieh - co-chair
  • Mong-Na Lo Huang - advisor
  • Files
  • etd-0728103-143737.pdf
  • indicate access worldwide
    Date of Submission 2003-07-28

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