期刊
ANNALS OF STATISTICS
卷 33, 期 5, 页码 2344-2394出版社
INST MATHEMATICAL STATISTICS-IMS
DOI: 10.1214/009053605000000516
关键词
computer experiment; consistency; fixed-domain asymptotics; Gaussian random field; Matern-type covariance function; sieve maximum likelihood estimation
Stein [Statist. Sci. 4 (1989) 432-433] proposed the Matern-type Gaussian random fields as a very flexible class of models for computer experiments. This article considers a subclass of these models that are exactly once mean square differentiable. In particular, the likelihood function is determined in closed form, and under mild conditions the sieve maximum likelihood estimators for the parameters of the covariance function are shown to be weakly consistent with respect to fixed-domain asymptotics.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据