| Constructing priors that penalize the complexity of Gaussian random fields GA Fuglstad, D Simpson, F Lindgren, H Rue Journal of the American Statistical Association 114 (525), 445-452, 2019 | 439 | 2019 |
| 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 | 374 | 2018 |
| Does non-stationary spatial data always require non-stationary random fields? GA Fuglstad, D Simpson, F Lindgren, H Rue Spatial Statistics 14, 505-531, 2015 | 139* | 2015 |
| Exploring a new class of non-stationary spatial Gaussian random fields with varying local anisotropy GA Fuglstad, F Lindgren, D Simpson, H Rue Statistica Sinica, 115-133, 2015 | 139 | 2015 |
| Predicting soil properties in the Canadian boreal forest with limited data: Comparison of spatial and non-spatial statistical approaches J Beguin, GA Fuglstad, N Mansuy, D Paré Geoderma 306, 195-205, 2017 | 81 | 2017 |
| Assessing comorbidity and correlates of wasting and stunting among children in Somalia using cross-sectional household surveys: 2007 to 2010 DK Kinyoki, NB Kandala, SO Manda, ET Krainski, GA Fuglstad, ... Bmj Open 6 (3), e009854, 2016 | 77 | 2016 |
| Estimating under-five mortality in space and time in a developing world context J Wakefield, GA Fuglstad, A Riebler, J Godwin, K Wilson, SJ Clark Statistical methods in medical research 28 (9), 2614-2634, 2019 | 70 | 2019 |
| Predominant regional biophysical cooling from recent land cover changes in Europe B Huang, X Hu, GA Fuglstad, X Zhou, W Zhao, F Cherubini Nature communications 11 (1), 1066, 2020 | 69 | 2020 |
| Intuitive joint priors for variance parameters GA Fuglstad, IG Hem, A Knight, H Rue, A Riebler | 38* | 2020 |
| Design-and model-based approaches to small-area estimation in a low-and middle-income country context: comparisons and recommendations J Paige, GA Fuglstad, A Riebler, J Wakefield Journal of Survey Statistics and Methodology 10 (1), 50-80, 2022 | 31 | 2022 |
| Landscape relatedness: detecting contemporary fine-scale spatial structure in wild populations AJ Norman, AV Stronen, GA Fuglstad, A Ruiz-Gonzalez, J Kindberg, ... Landscape Ecology 32, 181-194, 2017 | 23 | 2017 |
| 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 |
| Compression of climate simulations with a nonstationary global SpatioTemporal SPDE model GA Fuglstad, S Castruccio The Annals of Applied Statistics 14 (2), 542-559, 2020 | 13 | 2020 |
| Environmental mapping using Bayesian spatial modelling (INLA/SPDE): A reply to Huang et al.(2017). GA Fuglstad, J Beguin The Science of the Total Environment 624, 596-598, 2017 | 11 | 2017 |
| The two cultures for prevalence mapping: small area estimation and spatial statistics GA Fuglstad, ZR Li, J Wakefield arXiv preprint arXiv:2110.09576, 2021 | 10 | 2021 |
| Spatial aggregation with respect to a population distribution: Impact on inference J Paige, GA Fuglstad, A Riebler, J Wakefield Spatial Statistics 52, 100714, 2022 | 9 | 2022 |
| Spatial modelling and inference with spde-based gmrfs GA Fuglstad Institutt for matematiske fag, 2011 | 9 | 2011 |
| Robust modeling of additive and nonadditive variation with intuitive inclusion of expert knowledge IG Hem, ML Selle, G Gorjanc, GA Fuglstad, A Riebler Genetics 217 (3), iyab002, 2021 | 8* | 2021 |
| Space-time smoothing of demographic and health indicators using the R package SUMMER ZR Li, BD Martin, TQ Dong, GA Fuglstad, J Paige, A Riebler, S Clark, ... arXiv preprint arXiv:2007.05117, 2020 | 8 | 2020 |
| A stochastic locally diffusive model with neural network‐based deformations for global sea surface temperature W Hu, GA Fuglstad, S Castruccio Stat 11 (1), e431, 2022 | 5 | 2022 |
Andrea RieblerDepartment of Mathematical Sciences, NTNU, Trondheim, NorwayVerified email at math.ntnu.no
