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※ [本文轉錄自 NCTU-STAT96G 看板]
清華大學、交通大學
統 計 學 研 究 所
專 題 演 講
題 目: Componentwise Variance Dispersion Graphs for Mixture Experiments
主講人: Prof. John J. Borkowski
Department of Mathematical Sciences
Montana State University
時 間: 97年8月6日（星期三）10：40 - 11：30
（上午10：20-10：40茶會於統計所821室舉行）
地 點: 清大綜合三館837室
Abstract
Much research has been devoted to graphical methods for comparison of
prediction properties of response surface (RS) designs for experiments in
spherical and cuboidal design spaces (Borkowski 2006). In these experiments,
the design factor settings can be varied independently. Consider, however, a
q-component mixture experiment constraints defined by lower and upper bounds
( for component proportion (i = 1, 2, …, q). For a mixture experiment,
there is also the additional constraint that the sum of component proportions
must equal 1 (). Whether the design region for a mixture experiment is a
simplex or some irregularly shaped subregion of the simplex defined by these
constraints, the problem of interest addressed in this research is the
extension of variance dispersion graphs (VDGs) to experiments involving
mixtures. As an alternative to studing the prediction variance on shrunken
polyhedral spaces (Piepel and Anderson 1993), a new graphical tool, called
the Componentwise variance dispersion graph (CVDG), will be proposed.
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