Some covariance models based on normal scale mixtures
Statistics Theory
2011-02-28 v1 Statistics Theory
Abstract
Modelling spatio-temporal processes has become an important issue in current research. Since Gaussian processes are essentially determined by their second order structure, broad classes of covariance functions are of interest. Here, a new class is described that merges and generalizes various models presented in the literature, in particular models in Gneiting (J. Amer. Statist. Assoc. 97 (2002) 590--600) and Stein (Nonstationary spatial covariance functions (2005) Univ. Chicago). Furthermore, new models and a multivariate extension are introduced.
Cite
@article{arxiv.1102.5228,
title = {Some covariance models based on normal scale mixtures},
author = {Martin Schlather},
journal= {arXiv preprint arXiv:1102.5228},
year = {2011}
}
Comments
Published in at http://dx.doi.org/10.3150/09-BEJ226 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)