Journal
STATISTICS AND COMPUTING
Volume 22, Issue 3, Pages 739-751Publisher
SPRINGER
DOI: 10.1007/s11222-010-9202-3
Keywords
Asymptotic distribution; Response surface methodology; Second-order polynomial model; Unconstrained optimization
Ask authors/readers for more resources
Response surface methodology aims at finding the combination of factor levels which optimizes a response variable. A second order polynomial model is typically employed to make inference on the stationary point of the true response function. A suitable reparametrization of the polynomial model, where the coordinates of the stationary point appear as the parameter of interest, is used to derive unconstrained confidence regions for the stationary point. These regions are based on the asymptotic normal approximation to the sampling distribution of the maximum likelihood estimator of the stationary point. A simulation study is performed to evaluate the coverage probabilities of the proposed confidence regions. Some comparisons with the standard confidence regions due to Box and Hunter are also showed.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available