Noninformative Bayesian estimation for the optimum in a single factor quadratic response model

研究成果: 雜誌貢獻期刊論文同行評審

2 引文 斯高帕斯(Scopus)

摘要

The estimation of the location and magnitude of the optimum has long been considered as an important problem in the realm of response surface methodology. In this paper, we consider the Bayes estimates in a single factor quadratic response function, after a reparametrization from the linear model, using noninformative priors. The usual constant noninformative prior for the reparametrized model does not yield a proper posterior, thus it is desirable to consider other noninformative priors such as the Jeffreys prior and reference priors. Comparisons will be made based on the resulting posterior means, variances and credible intervals by examples and simulations.

原文???core.languages.en_GB???
頁(從 - 到)225-240
頁數16
期刊Test
10
發行號2
DOIs
出版狀態已出版 - 12月 2001

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