Abstract
Mixture Experiments provide a foundation to optimize the predicted response basedon blends of different components . Parody and Edwards (2006) gave a method of inference on the expected response of a 2nd-order rotatable design, utilizing a simulation-based critical point to give substantially sharper intervals when compared to the simultaneous confidence intervals provided by Sa and Edwards (1993). Here, we begin with discussing the theory of mixture experiments and pseudocomponents. Then we move on to review the literature of simulation-based methods forgenerating critical points and visualization techniques of general response surface designs. Next, we develop the simulation-based technique for a {q, 2} Simplex-Lattice Design and visualize the simulation-based confidence intervals for the expected improvement in response based on two examples. Finally, we compare theefficiency of the simulation-based critical points relative to Scheffé’s adaptation ofcritical points for the general response surface. We conclude by providing an efficiency table and demonstrate superiority of the simulation-based method over the Scheffé’s adaptation on the basis of sample size savings.
Library of Congress Subject Headings
Mixtures--Experiments; Mixtures--Statistical methods; Chemical processes--Mathematical models
Publication Date
4-19-2019
Document Type
Thesis
Student Type
Graduate
Degree Name
Applied Statistics (MS)
Department, Program, or Center
School of Mathematical Sciences (COS)
Advisor
Robert Parody
Recommended Citation
Bedi, Tejasv, "Simulation-Based Inference on Mixture Experiments" (2019). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/10004
Campus
RIT – Main Campus
Plan Codes
APPSTAT-MS
