A class of covariate- dependent spatiotemporal covariance functions for the analysis of daily ozone concentration

Reich, BJ; Eidsvik, Jo; Guindani, M; Nail, A; Schmidt, AM

HERO ID

2336775

Reference Type

Journal Article

Year

2011

Language

English

PMID

24772199

HERO ID 2336775
In Press No
Year 2011
Title A class of covariate- dependent spatiotemporal covariance functions for the analysis of daily ozone concentration
Authors Reich, BJ; Eidsvik, Jo; Guindani, M; Nail, A; Schmidt, AM
Journal Annals of Applied Statistics
Volume 5
Issue 4
Page Numbers 2425-2447
Abstract In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. However, these assumptions are often untenable in practice because of the influence of local effects in the correlation structure. Therefore, it has been of prolonged interest in the literature to provide flexible and effective ways to model non-stationarity in the spatial effects. Arguably, due to the local nature of the problem, we might envision that the correlation structure would be highly dependent on local characteristics of the domain of study, namely the latitude, longitude and altitude of the observation sites, as well as other locally defined covariate information. In this work, we provide a flexible and computationally feasible way for allowing the correlation structure of the underlying processes to depend on local covariate information. We discuss the properties of the induced covariance functions and discuss methods to assess its dependence on local covariate information by means of a simulation study and the analysis of data observed at ozone-monitoring stations in the Southeast United States.
Doi 10.1214/11-AOAS482
Pmid 24772199
Wosid WOS:000300382800009
Is Certified Translation No
Dupe Override No
Is Public Yes
Language Text English
Keyword Covariance estimation; nonstationarity; ozone; spatial data analysis