Cross-covariance functions for multivariate random fields based on latent dimensions

168 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A Valid Matérn Class of Cross-Covariance Functions for Multivariate Random Fields With Any Number of Components (2012, methodology): “Apanasovich and Genton (2010) provided generic approaches to building asymmetric cross-covariance models.”
Matérn Cross-Covariance Functions for Multivariate Random Fields (2010, methodology): “A complementary description of the smoothness of a Matérn field is via the Hausdorff or fractal dimension of a sample path in Rd , which equals the maximum of d and d + 1 − ν (Adler 1981; Goff and Jordan 1988).”
Non‐stationary Cross‐Covariance Models for Multivariate Processes on a Globe (2011, methodology): “1 Covariance models for multivariate spatial processes Linear model of coregionalization: Schmidt and Gelfand (2003), Gelfand et al. (2004),... Convolution models: Majumdar et al. (2009) Reich and Fuentes (2007): semiparametric approach with separable covariance structure Gneiting et al. (2009): mul”
Modeling Nonstationary Processes Through Dimension Expansion (2010, methodology): “Speciﬁcally, Apanasovich and Genton (2010) use latent dimensions for the diﬀerent variables in order to build a class of valid cross-covariance functions.”
Classes of compactly supported covariance functions for multivariate random fields (2015, background): “The literature on this subject is sparse, with the work of Apanasovich and Genton (2010) and their more general versions in Porcu et al. (2006), being notable exceptions.”