Daniela Castro-Camilo
Title
Cited by
Cited by
Year
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
1332018
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
742017
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
242019
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
242018
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
18*2019
Spectral density regression for bivariate extremes
D Castro-Camilo, M de Carvalho
Stochastic environmental research and risk assessment 31 (7), 1603-1613, 2017
152017
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
92019
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 (1), 105-128, 2021
72021
Discussion of "Using Stacking to Average Bayesian Predictive Distributions" by Yao et. al
H Bakka, D Castro-Camilo, M Franco-Villoria, A Freni-Sterrantino, ...
3*2018
Local likelihood estimation of complex tail dependence structures in high dimensions, applied to US precipitation extremes
DC Camilo, R Huser
Taylor and Francis, 2019
22019
Bayesian computing with INLA
H Rue, D Castro-Camilo
22014
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
2021
Modelling Block Maxima With the Blended Generalised Extreme Value Distribution
SM Vandeskog, S Martino, D Castro-Camilo
2021
Practical strategies for GEV-based regression models for extremes
D Castro-Camilo, R Huser, H Rue
arXiv preprint arXiv:2106.13110, 2021
2021
Modelling short-term precipitation extremes with the blended generalised extreme value distribution
SM Vandeskog, S Martino, D Castro-Camilo, H Rue
arXiv preprint arXiv:2105.09062, 2021
2021
Landslide size matters: a new spatial predictive paradigm
L Lombardo, H Tanyas, R Huser, F Guzzetti, DC Camilo
EarthArXiv, 2021
2021
Blended GEV: a tutorial using R-INLA
D Castro-Camilo
A three-stage model for short-term extreme wind speed probabilistic forecasting
DC Camilo, R Huser, H Rue
The system can't perform the operation now. Try again later.
Articles 1–18