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Title: Fixed-domain asymptotics for a subclass of matérn-type gaussian random fields
Authors: Loh, W.-L. 
Keywords: Computer experiment
Fixed-domain asymptotics
Gaussian random field
Matérn-type covariance function
Sieve maximum likelihood estimation
Issue Date: Oct-2005
Citation: Loh, W.-L. (2005-10). Fixed-domain asymptotics for a subclass of matérn-type gaussian random fields. Annals of Statistics 33 (5) : 2344-2394. ScholarBank@NUS Repository.
Abstract: Stein [Statist. Sci. 4 (1989) 432-433] proposed the Matérn-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. © Institute of Mathematical Statistics, 2005.
Source Title: Annals of Statistics
ISSN: 00905364
DOI: 10.1214/009053605000000516
Appears in Collections:Staff Publications

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