Please use this identifier to cite or link to this item:
|Title:||Estimating structured correlation matrices in smooth Gaussian random field models|
|Authors:||Loh, W.-L. |
Sieve maximum likelihood estimation
Smooth Gaussian random field
Structured correlation matrix
|Source:||Loh, W.-L.,Lam, T.-K. (2000). Estimating structured correlation matrices in smooth Gaussian random field models. Annals of Statistics 28 (3) : 880-904. ScholarBank@NUS Repository.|
|Abstract:||This article considers the estimation of structured correlation matrices in infinitely differentiable Gaussian random field models. The problem is essentially motivated by the stochastic modeling of smooth deterministic responses in computer experiments. In particular, the log-likelihood function is determined explicitly in closed-form and the sieve maximum likelihood estimators are shown to be strongly consistent under mild conditions.|
|Source Title:||Annals of Statistics|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Feb 17, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.