| 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 | 187 | 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 | 178 | 2016 |
| 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 | 114 | 2019 |
| Spatial relationships between two georeferenced variables: With applications in R R Vallejos, F Osorio, M Bevilacqua Springer Nature, 2020 | 97 | 2020 |
| Comparing composite likelihood methods based on pairs for spatial Gaussian random fields M Bevilacqua, C Gaetan Statistics and Computing 25, 877-892, 2015 | 79 | 2015 |
| 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 | 66 | 2015 |
| Analysis of random fields using CompRandFld SA Padoan, M Bevilacqua Journal of Statistical Software 63, 1-27, 2015 | 47 | 2015 |
| Radial basis functions with compact support for multivariate geostatistics E Porcu, DJ Daley, M Buhmann, M Bevilacqua Stochastic environmental research and risk assessment 27, 909-922, 2013 | 45 | 2013 |
| Covariance functions that are stationary or nonstationary in space and stationary in time E Porcu, J Mateu, M Bevilacqua Statistica Neerlandica 61 (3), 358-382, 2007 | 40 | 2007 |
| Modelling residuals dependence in dynamic life tables: A geostatistical approach A Debón, F Montes, J Mateu, E Porcu, M Bevilacqua Computational Statistics & Data Analysis 52 (6), 3128-3147, 2008 | 33 | 2008 |
| Covariance tapering for multivariate Gaussian random fields estimation M Bevilacqua, A Fassò, C Gaetan, E Porcu, D Velandia Statistical Methods & Applications 25, 21-37, 2016 | 32 | 2016 |
| Non‐Gaussian geostatistical modeling using (skew) t processes M Bevilacqua, C Caamaño‐Carrillo, RB Arellano‐Valle, V Morales‐Oñate Scandinavian Journal of Statistics 48 (1), 212-245, 2021 | 29 | 2021 |
| Unifying compactly supported and Matérn covariance functions in spatial statistics M Bevilacqua, C Caamaño-Carrillo, E Porcu Journal of Multivariate Analysis 189, 104949, 2022 | 26 | 2022 |
| On the flexibility of multivariate covariance models: comment on the paper by Genton and Kleiber M Bevilacqua, AS Hering, E Porcu Statistical Science 30 (2), 167-169, 2015 | 26 | 2015 |
| The Matérn model: A journey through statistics, numerical analysis and machine learning E Porcu, M Bevilacqua, R Schaback, CJ Oates Statistical Science 39 (3), 469-492, 2024 | 24 | 2024 |
| Nonseparable, space-time covariance functions with dynamical compact supports E Porcu, M Bevilacqua, MG Genton Statistica Sinica 30 (2), 719-739, 2020 | 24 | 2020 |
| Fitting negative spatial covariances to geothermal field temperatures in Nea Kessani (Greece) J Mateu, E Porcu, G Christakos, M Bevilacqua Environmetrics: The official journal of the International Environmetrics …, 2007 | 20 | 2007 |
| Equivalence and orthogonality of Gaussian measures on spheres A Arafat, E Porcu, M Bevilacqua, J Mateu Journal of Multivariate Analysis 167, 306-318, 2018 | 19 | 2018 |
| Composite likelihood inference for multivariate Gaussian random fields M Bevilacqua, A Alegria, D Velandia, E Porcu Journal of agricultural, biological, and environmental statistics 21, 448-469, 2016 | 19 | 2016 |
| Buhmann covariance functions, their compact supports, and their smoothness E Porcu, P Zastavyi, M Bevilacqua arXiv preprint arXiv:1606.09527, 2016 | 18 | 2016 |
