Accounting for Mixture Errors in Analyzing Mixture Experiments

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.

• Bayesian Method
• Error-in-Variables
• MCMC

Additional information

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].