On some matérn covariance functions for spatio-temporal random fields

Ryan H.L. Ip, W.K Li

Research output: Contribution to journalArticle

3 Citations (Scopus)
14 Downloads (Pure)

Abstract

The Matern class is an important class of covariance functions in spatial statistics. With the recent flourishing trend in modelling spatio-temporal data, indepth theoretical development of spatio-temporal covariograms is needed. In this paper, theories under the infill asymptotic framework concerning estimation issues of a generally non-separable Matern class of spatio-temporal covariance function is presented. It is found that not all parameters can be estimated consistently while quantities that can be estimated consistently are found based on equivalence and orthogonality of Gaussian measures. The micro-ergodic parameters are found to be different when the degrees of separability between the space and time components are different. For the computation, an easy-to-implement estimation procedure is given. Simulation studies are conducted to show how well the asymptotic results apply when the sample size is moderate. A set of air pollution data is used to demonstrate the usefulness of the estimation procedure suggested.
Original languageEnglish
Pages (from-to)805-822
Number of pages18
JournalStatistica Sinica
Volume27
Issue number2
DOIs
Publication statusPublished - Apr 2017

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