Bayesian Treed Gaussian Process Models With an Application to Computer Modeling

被引:386
作者
Gramacy, Robert B. [1 ]
Lee, Herbert K. H. [2 ]
机构
[1] Univ Cambridge, Stat Lab, Cambridge CB2 1SB, England
[2] Univ Calif Santa Cruz, Dept Appl Math & Stat, Santa Cruz, CA 95064 USA
基金
美国国家航空航天局; 美国国家科学基金会;
关键词
Computer simulator; Nonparametric regression; Nonstationary spatial model; Recursive partioning;
D O I
10.1198/016214508000000689
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Motivated by a computer experiment for the design of a rocket booster this article explores nonstationary modeling methodologies that couple stationary Gaussian processes with treed partioning is a simple but effective method for dealing with nonstationarity. The methodological developments and statistical computing details that make this approach efficient are described in detail. In addition to providing an analysis of the rocket booster, we show that our approach is effective in other areas as well.
引用
收藏
页码:1119 / 1130
页数:12
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