Emilio Porcu
Emilio Porcu
Professor of Statistics, KU Abu Dhabi, & Visiting Fellow, Trinity College, Dublin
Verified email at ku.ac.ae - Homepage
Cited by
Cited by
Estimating space and space-time covariance functions for large data sets: a weighted composite likelihood approach
M Bevilacqua, C Gaetan, J Mateu, E Porcu
Journal of the American Statistical Association 107 (497), 268-280, 2012
Spatio-temporal covariance and cross-covariance functions of the great circle distance on a sphere
E Porcu, M Bevilacqua, MG Genton
Journal of the American Statistical Association 111 (514), 888-898, 2016
Nonseparable stationary anisotropic space–time covariance functions
E Porcu, P Gregori, J Mateu
Stochastic Environmental Research and Risk Assessment 21 (2), 113-122, 2006
From Schoenberg coefficients to Schoenberg functions
C Berg, E Porcu
Constructive Approximation 45 (2), 217-241, 2017
New classes of covariance and spectral density functions for spatio-temporal modelling
E Porcu, J Mateu, F Saura
Stochastic Environmental Research and Risk Assessment 22 (1), 65-79, 2008
Quasi-arithmetic means of covariance functions with potential applications to space–time data
E Porcu, J Mateu, G Christakos
Journal of Multivariate Analysis 100 (8), 1830-1844, 2009
The Dagum family of isotropic correlation functions
C Berg, J Mateu, E Porcu
Bernoulli 14 (4), 1134-1149, 2008
Estimation and prediction using generalized Wendland covariance functions under fixed domain asymptotics
M Bevilacqua, T Faouzi, R Furrer, E Porcu
The Annals of Statistics 47 (2), 828-856, 2019
An improved spectral turning-bands algorithm for simulating stationary vector Gaussian random fields
X Emery, D Arroyo, E Porcu
Stochastic environmental research and risk assessment 30 (7), 1863-1873, 2016
Modeling temporally evolving and spatially globally dependent data
E Porcu, A Alegria, R Furrer
International Statistical Review 86 (2), 344-377, 2018
Modelling spatio-temporal data: a new variogram and covariance structure proposal
E Porcu, J Mateu, A Zini, R Pini
Statistics & probability letters 77 (1), 83-89, 2007
Predicting genetic values: a kernel-based best linear unbiased prediction with genomic data
U Ober, M Erbe, N Long, E Porcu, M Schlather, H Simianer
Genetics 188 (3), 695-708, 2011
Classes of compactly supported covariance functions for multivariate random fields
DJ Daley, E Porcu, M Bevilacqua
Stochastic Environmental Research and Risk Assessment 29 (4), 1249-1263, 2015
Dimension walks and Schoenberg spectral measures
D Daley, E Porcu
Proceedings of the American Mathematical Society 142 (5), 1813-1824, 2014
Characterization theorems for some classes of covariance functions associated to vector valued random fields
E Porcu, V Zastavnyi
Journal of Multivariate Analysis 102 (9), 1293-1301, 2011
On potentially negative space time covariances obtained as sum of products of marginal ones
P Gregori, E Porcu, J Mateu, Z Sasvári
Annals of the Institute of Statistical Mathematics 60 (4), 865-882, 2008
Radial basis functions with compact support for multivariate geostatistics
E Porcu, DJ Daley, M Buhmann, M Bevilacqua
Stochastic environmental research and risk assessment 27 (4), 909-922, 2013
Recent advances to model anisotropic space–time data
J Mateu, E Porcu, P Gregori
Statistical Methods and Applications 17 (2), 209-223, 2008
Determinantal point process models on the sphere
J Møller, M Nielsen, E Porcu, E Rubak
Bernoulli 24 (2), 1171-1201, 2018
A flexible class of non-separable cross-covariance functions for multivariate space–time data
M Bourotte, D Allard, E Porcu
Spatial Statistics 18, 125-146, 2016
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