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 | 184 | 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 | 177 | 2016 |
Statistical challenges of administrative and transaction data DJ Hand Journal of the Royal Statistical Society Series A: Statistics in Society 181 …, 2018 | 168 | 2018 |
Nonseparable stationary anisotropic space–time covariance functions E Porcu, P Gregori, J Mateu Stochastic Environmental Research and Risk Assessment 21 (2), 113-122, 2006 | 112 | 2006 |
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 | 105 | 2019 |
From Schoenberg coefficients to Schoenberg functions C Berg, E Porcu Constructive Approximation 45, 217-241, 2017 | 95 | 2017 |
Modeling temporally evolving and spatially globally dependent data E Porcu, A Alegria, R Furrer International Statistical Review 86 (2), 344-377, 2018 | 94 | 2018 |
RETRACTED ARTICLE: Application of extreme learning machine for estimation of wind speed distribution S Shamshirband, K Mohammadi, CW Tong, D Petković, E Porcu, ... Climate dynamics 46, 1893-1907, 2016 | 83 | 2016 |
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, 1863-1873, 2016 | 79 | 2016 |
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 | 76 | 2009 |
The Dagum family of isotropic correlation functions C Berg, J Mateu, E Porcu | 76 | 2008 |
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 (Suppl 1), 65-79, 2008 | 75 | 2008 |
30 Years of space–time covariance functions E Porcu, R Furrer, D Nychka Wiley Interdisciplinary Reviews: Computational Statistics 13 (2), e1512, 2021 | 71 | 2021 |
Dimension walks and Schoenberg spectral measures D Daley, E Porcu Proceedings of the American Mathematical Society 142 (5), 1813-1824, 2014 | 66 | 2014 |
Classes of compactly supported covariance functions for multivariate random fields DJ Daley, E Porcu, M Bevilacqua Stochastic Environmental Research and Risk Assessment 29, 1249-1263, 2015 | 64 | 2015 |
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 | 63 | 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 | 61 | 2011 |
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 | 54 | 2011 |
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 | 51 | 2016 |
Anisotropy models for spatial data D Allard, R Senoussi, E Porcu Mathematical Geosciences 48, 305-328, 2016 | 48 | 2016 |