| Spatial modeling with R‐INLA: A review H Bakka, H Rue, GA Fuglstad, A Riebler, D Bolin, J Illian, E Krainski, ... Wiley Interdisciplinary Reviews: Computational Statistics 10 (6), e1443, 2018 | 384 | 2018 |
| 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 | 335 | 2018 |
| Changes in soil organic carbon under perennial crops A Ledo, P Smith, A Zerihun, J Whitaker, JL Vicente‐Vicente, Z Qin, ... Global change biology 26 (7), 4158-4168, 2020 | 204 | 2020 |
| Non-stationary Gaussian models with physical barriers H Bakka, J Vanhatalo, JB Illian, D Simpson, H Rue Spatial statistics 29, 268-288, 2019 | 144* | 2019 |
| 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 | 117 | 2018 |
| 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 | 71 | 2019 |
| Landslide susceptibility maps of Italy: Lesson learnt from dealing with multiple landslide types and the uneven spatial distribution of the national inventory M Loche, M Alvioli, I Marchesini, H Bakka, L Lombardo Earth-Science Reviews 232, 104125, 2022 | 65 | 2022 |
| New frontiers in Bayesian modeling using the INLA package in R J Van Niekerk, H Bakka, H Rue, O Schenk arXiv preprint arXiv:1907.10426, 2019 | 63 | 2019 |
| Approximate Bayesian inference for analysis of spatiotemporal flood frequency data ÁV Jóhannesson, S Siegert, R Huser, H Bakka, B Hrafnkelsson The Annals of Applied Statistics 16 (2), 905-935, 2022 | 28 | 2022 |
| Competing risks joint models using R-INLA J Niekerk, H Bakka, H Rue Statistical Modelling 21 (1-2), 56-71, 2021 | 28 | 2021 |
| The emergence and shift in seasonality of Lyme borreliosis in Northern Europe A Goren, H Viljugrein, IM Rivrud, S Jore, H Bakka, Y Vindenes, ... Proceedings of the Royal Society B 290 (1993), 20222420, 2023 | 23 | 2023 |
| Max-and-smooth: A two-step approach for approximate Bayesian inference in latent Gaussian models B Hrafnkelsson, S Siegert, R Huser, H Bakka, ÁV Jóhannesson Bayesian Analysis 16 (2), 611-638, 2021 | 22 | 2021 |
| Inla: Full bayesian analysis of latent gaussian models using integrated nested laplace approximations H Rue, F Lindgren, D Simpson, S Martino, E Teixeira Krainski, H Bakka, ... R package version 19 (03), 2019 | 19 | 2019 |
| A diffusion-based spatio-temporal extension of Gaussian Mat\'ern fields F Lindgren, H Bakka, D Bolin, E Krainski, H Rue arXiv preprint arXiv:2006.04917, 2020 | 18 | 2020 |
| Dealing with physical barriers in bottlenose dolphin (Tursiops truncatus) distribution J Martínez-Minaya, D Conesa, H Bakka, MG Pennino Ecological Modelling 406, 44-49, 2019 | 16 | 2019 |
| High-resolution Bayesian mapping of landslide hazard with unobserved trigger event T Opitz, H Bakka, R Huser, L Lombardo The Annals of Applied Statistics 16 (3), 1653-1675, 2022 | 15 | 2022 |
| The diffusion-based extension of the Matérn field to space-time H Bakka, E Krainski, D Bolin, H Rue, F Lindgren arXiv preprint arXiv:2006.04917 4 (10), 2020 | 15 | 2020 |
| Revisiting area risk classification of visceral leishmaniasis in Brazil G Machado, J Alvarez, HC Bakka, A Perez, LE Donato, ... BMC infectious diseases 19, 1-9, 2019 | 15 | 2019 |
| How to solve the stochastic partial differential equation that gives a Mat\'ern random field using the finite element method H Bakka arXiv preprint arXiv:1803.03765, 2018 | 15 | 2018 |
| A principled distance-based prior for the shape of the Weibull model J Van Niekerk, H Bakka, H Rue Statistics & Probability Letters 174, 109098, 2021 | 14 | 2021 |
Håvard RueKing Abdullah University of Science and TechnologyE-mail confirmado em kaust.edu.sa
