| Advanced spatial modeling with stochastic partial differential equations using R and INLA E Krainski, V Gómez-Rubio, H Bakka, A Lenzi, D Castro-Camilo, ... Chapman and Hall/CRC, 2018 | 272 | 2018 |
| Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model D Castro-Camilo, L Lombardo, PM Mai, J Dou, R Huser Environmental modelling & software 97, 145-156, 2017 | 125 | 2017 |
| Accounting for covariate distributions in slope-unit-based landslide susceptibility models. A case study in the alpine environment G Amato, C Eisank, D Castro-Camilo, L Lombardo Engineering geology 260, 105237, 2019 | 56 | 2019 |
| Landslide size matters: A new data-driven, spatial prototype L Lombardo, H Tanyas, R Huser, F Guzzetti, D Castro-Camilo Engineering Geology 293, 106288, 2021 | 44 | 2021 |
| Local likelihood estimation of complex tail dependence structures in high dimensions, applied to US precipitation extremes D Castro-Camilo, R Huser Journal of the American Statistical Association, 2019 | 41* | 2019 |
| Time-Varying Extreme Value Dependence with Application to Leading European Stock Markets D Castro-Camilo, M de Carvalho, J Wadsworth arXiv preprint arXiv:1709.01198, 2018 | 39 | 2018 |
| A spliced gamma-generalized Pareto model for short-term extreme wind speed probabilistic forecasting D Castro-Camilo, R Huser, H Rue Journal of Agricultural, Biological and Environmental Statistics 24 (3), 517-534, 2019 | 28 | 2019 |
| Practical strategies for generalized extreme value‐based regression models for extremes D Castro‐Camilo, R Huser, H Rue Environmetrics 33 (6), e2742, 2022 | 23 | 2022 |
| Spectral density regression for bivariate extremes D Castro-Camilo, M de Carvalho Stochastic environmental research and risk assessment 31 (7), 1603-1613, 2017 | 17 | 2017 |
| Bayesian space-time gap filling for inference on extreme hot-spots: an application to Red Sea surface temperatures D Castro-Camilo, L Mhalla, T Opitz Extremes 24, 105-128, 2021 | 11 | 2021 |
| Modelling short-term precipitation extremes with the blended generalised extreme value distribution SM Vandeskog, S Martino, D Castro-Camilo, H Rue arXiv, 2021 | 10 | 2021 |
| Modelling sub-daily precipitation extremes with the blended generalised extreme value distribution SM Vandeskog, S Martino, D Castro-Camilo, H Rue Journal of Agricultural, Biological and Environmental Statistics 27 (4), 598-621, 2022 | 8 | 2022 |
| Unified landslide hazard assessment using hurdle models: a case study in the Island of Dominica E Bryce, L Lombardo, C van Westen, H Tanyas, D Castro-Camilo Stochastic Environmental Research and Risk Assessment 36 (8), 2071-2084, 2022 | 7 | 2022 |
| Modelling block maxima with the blended generalised extreme value distribution SM Vandeskog, S Martino, D Castro-Camilo | 4 | 2021 |
| Bayesian computing with INLA H Rue, D Castro-Camilo Pacote R Versão 1, 2018 | 2 | 2018 |
| On the estimation of landslide intensity, hazard and density via data-driven models M Di Napoli, H Tanyas, D Castro-Camilo, D Calcaterra, A Cevasco, ... | 1 | 2023 |
| Spatiotemporal data science: theoretical advances and applications F Amato, L Lombardo, M Tonini, A Marvuglia, D Castro-Camilo, ... Stochastic Environmental Research and Risk Assessment 36 (8), 2027-2029, 2022 | | 2022 |
| Landslide size matters: a new spatial predictive paradigm L Lombardo, H Tanyas, R Huser, F Guzzetti, D Castro-Camilo EarthArXiv, 2021 | | 2021 |
| Discussion of "Using Stacking to Average Bayesian Predictive Distributions" by Yao et. al H Bakka, D Castro-Camilo, M Franco-Villoria, A Freni-Sterrantino, ... | | 2018 |
| Blended GEV: a tutorial using R-INLA D Castro-Camilo | | |
Håvard RueKing Abdullah University of Science and TechnologyVerifierad e-postadress på kaust.edu.sa
