STATISTICS SEMINAR SERIES :: A Bayesian Approach to the Design and Analysis of Fractionated Experiments

Event Details
  • Date/Time:
    • Thursday September 22, 2005
      11:00 am - 12:00 am
  • Location: Executive Classroom #228
  • Phone:
  • URL:
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  • Fee(s):
    N/A
  • Extras:
Contact
Barbara Christopher
Industrial and Systems Engineering
Contact Barbara Christopher
404.385.3102
Summaries

Summary Sentence: STATISTICS SEMINAR SERIES :: A Bayesian Approach to the Design and Analysis of Fractionated Experiments

Full Summary: STATISTICS SEMINAR SERIES :: A Bayesian Approach to the Design and Analysis of Fractionated Experiments

Specifying a prior distribution for the large number of parameters in the statistical model is a critical step in a Bayesian approach to the design and analysis of experiments. This article shows that the prior distribution can be induced from a functional prior on the underlying transfer function. The functional prior requires the specification of only a few hyper-parameters and therefore, can be easily implemented in practice. The usefulness of the approach is demonstrated through the analysis of some experiments. The article also proposes a new class of design criteria and establishes their connections with the minimum aberration criterion.

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H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Seminar/Lecture/Colloquium
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Status
  • Created By: Barbara Christopher
  • Workflow Status: Published
  • Created On: Oct 8, 2010 - 7:38am
  • Last Updated: Oct 7, 2016 - 9:52pm