@article{693f9285f64d44188a347134c9230df8,
title = "The Shkarofsky-Gneiting class of covariance models for bivariate Gaussian random fields",
abstract = "We propose new covariance functions for bivariate Gaussian random fields that are very general and include as special cases other popular models proposed in earlier literature, namely, the bivariate Mat{\'e}rn and bivariate Cauchy models. The proposed model allows the covariance margins to belong to different parametric families with. To our knowledge, this is the first model of this type to be proposed in the literature. For instance, one of the margins can be of the Mat{\'e}rn type, whereas the latter can index long-range dependence. Estimation of the model is illustrated through simulation.",
keywords = "Mat{\'e}rn, bivariate covariance functions, generalized Cauchy, long-range dependence, smoothness",
author = "Emilio Porcu and Moreno Bevilacqua and Hering, {Amanda S.}",
note = "Funding Information: FONDECYT, Grant/Award Number: 1160280 and 1170290; Iniciativa Cient{\'i}fica Milenio-Minecon Nucleo Milenio MESCD. Funding Information: This research was prompted while Emilio Porcu was visiting the Department of Statistical Science at Baylor University. The research work conducted by Moreno Bevilacqua and Emilio Porcu was supported respectively by FONDECYT Grants 1160280 and 1170290, Chile. For both, the project is currently supported by Iniciativa Cient{\'i}fica Milenio - Minecon Nucleo Milenio MESCD. We are grateful to the Associate Editor and a Referee for their comments. Publisher Copyright: {\textcopyright} 2018 John Wiley & Sons, Ltd.",
year = "2018",
doi = "10.1002/STA4.207",
language = "English",
volume = "7",
journal = "Stat",
issn = "2049-1573",
publisher = "Wiley-Blackwell Publishing Ltd",
number = "1",
}