Abstract
Until now, mixture errors that cause the actual mixture proportions to differ from those intended have not been considered in the analysis of mixture experiments. In this article, we show how a Bayesian approach can account for such errors. A simulation study shows the problems with ignoring these errors and also the benefits of accounting for them. The proposed approach is illustrated with a semirealistic glass mixture experiment.
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Notes on contributors
M. Hamada
Dr. Hamada is a Technical Staff Member in Statistical Sciences. He is a member of ASQ. His email address is [email protected].
H. F. Martz
Dr. Martz is a Laboratory Associate in Statistical Sciences. His email address is [email protected].
S. Steiner
Dr. Steiner is an Associate Professor in the Department of Statistics and Actuarial Science. He is a member of ASQ. His email address is [email protected].