Forecasting uncertainty in electricity smart meter data by boosting additive quantile regression SB Taieb, R Huser, RJ Hyndman, MG Genton IEEE Transactions on Smart Grid 7 (5), 2448-2455, 2016 | 236 | 2016 |
Space–time modelling of extreme events R Huser, AC Davison Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2014 | 233 | 2014 |
Statistics of extremes AC Davison, R Huser Annual Review of Statistics and its Application 2 (1), 203-235, 2015 | 229 | 2015 |
Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection P Naveau, R Huser, P Ribereau, A Hannart Water Resources Research 52 (4), 2753-2769, 2016 | 170 | 2016 |
Composite likelihood estimation for the Brown–Resnick process R Huser, AC Davison Biometrika 100 (2), 511-518, 2013 | 161 | 2013 |
Modeling spatial processes with unknown extremal dependence class R Huser, JL Wadsworth Journal of the American statistical association 114 (525), 434-444, 2019 | 140 | 2019 |
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 Modeling & Software 97, 145-156, 2017 | 132* | 2017 |
Space-time landslide predictive modelling L Lombardo, T Opitz, F Ardizzone, F Guzzetti, R Huser Earth-science reviews 209, 103318, 2020 | 131 | 2020 |
Geostatistics of dependent and asymptotically independent extremes AC Davison, R Huser, E Thibaud Mathematical Geosciences 45, 511-529, 2013 | 125 | 2013 |
High-order composite likelihood inference for max-stable distributions and processes S Castruccio, R Huser, MG Genton Journal of Computational and Graphical Statistics 25 (4), 1212-1229, 2016 | 122 | 2016 |
Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures R Huser, T Opitz, E Thibaud Spatial Statistics 21 (A), 166-186, 2017 | 115 | 2017 |
INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles T Opitz, R Huser, H Bakka, H Rue Extremes 21 (3), 441-462, 2018 | 112 | 2018 |
Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster L Lombardo, T Opitz, R Huser Stochastic Environmental Research and Risk Assessment 32 (7), 2179-2198, 2018 | 100 | 2018 |
Factor copula models for replicated spatial data P Krupskii, R Huser, MG Genton Journal of the American Statistical Association 113 (521), 467-479, 2018 | 98 | 2018 |
Non-stationary dependence structures for spatial extremes R Huser, MG Genton Journal of Agricultural, Biological, and Environmental Statistics 21 (3 …, 2016 | 94 | 2016 |
Advances in statistical modeling of spatial extremes R Huser, JL Wadsworth Wiley Interdisciplinary Reviews: Computational Statistics 14 (1), e1537, 2022 | 88 | 2022 |
Likelihood estimators for multivariate extremes R Huser, AC Davison, MG Genton Extremes 19, 79-103, 2016 | 84 | 2016 |
Spatial extremes AC Davison, R Huser, E Thibaud Handbook of Environmental and Ecological Statistics, 711-744, 2019 | 81 | 2019 |
Full likelihood inference for max‐stable data R Huser, C Dombry, M Ribatet, MG Genton Stat 8 (1), e218, 2019 | 70 | 2019 |
Geostatistical modeling to capture seismic-shaking patterns from earthquake-induced landslides L Lombardo, H Bakka, H Tanyas, C van Westen, PM Mai, R Huser Journal of Geophysical Research: Earth Surface 124 (7), 1958-1980, 2019 | 68 | 2019 |