| Spatial autoregressive models for statistical inference from ecological data JM Ver Hoef, EE Peterson, MB Hooten, EM Hanks, MJ Fortin Ecological Monographs 88 (1), 36-59, 2018 | 232 | 2018 |
| Restricted spatial regression in practice: geostatistical models, confounding, and robustness under model misspecification EM Hanks, EM Schliep, MB Hooten, JA Hoeting Environmetrics 26 (4), 243-254, 2015 | 192 | 2015 |
| Continuous-time discrete-space models for animal movement EM Hanks, MB Hooten, MW Alldredge | 109 | 2015 |
| Circuit Theory and Model-Based Inference for Landscape Connectivity EM Hanks, MB Hooten Journal of the American Statistical Association 108 (501), 22-33, 2013 | 93 | 2013 |
| On the relationship between conditional (CAR) and simultaneous (SAR) autoregressive models JM Ver Hoef, EM Hanks, MB Hooten Spatial statistics 25, 68-85, 2018 | 86 | 2018 |
| Agent-based inference for animal movement and selection MB Hooten, DS Johnson, EM Hanks, JH Lowry Journal of Agricultural, Biological and Environmental Statistics 15, 523-538, 2010 | 86 | 2010 |
| Hierarchical animal movement models for population‐level inference MB Hooten, FE Buderman, BM Brost, EM Hanks, JS Ivan Environmetrics 27 (6), 322-333, 2016 | 75 | 2016 |
| Reconciling resource utilization and resource selection functions MB Hooten, EM Hanks, DS Johnson, MW Alldredge Journal of Animal Ecology 82 (6), 1146-1154, 2013 | 74 | 2013 |
| Velocity-based movement modeling for individual and population level inference EM Hanks, MB Hooten, DS Johnson, JT Sterling PLoS One 6 (8), e22795, 2011 | 74 | 2011 |
| Social, spatial and temporal organization in a complex insect society LE Quevillon, EM Hanks, S Bansal, DP Hughes Scientific reports 5 (1), 13393, 2015 | 72 | 2015 |
| Machine learning for modeling animal movement DA Wijeyakulasuriya, EW Eisenhauer, BA Shaby, EM Hanks PloS one 15 (7), e0235750, 2020 | 69 | 2020 |
| Animal movement constraints improve resource selection inference in the presence of telemetry error BM Brost, MB Hooten, EM Hanks, RJ Small Ecology 96 (10), 2590-2597, 2015 | 62 | 2015 |
| Effects of two centuries of global environmental variation on phenology and physiology of Arabidopsis thaliana VL DeLeo, DNL Menge, EM Hanks, TE Juenger, JR Lasky Global Change Biology 26 (2), 523-538, 2020 | 59 | 2020 |
| Dynamic spatio-temporal models for spatial data TJ Hefley, MB Hooten, EM Hanks, RE Russell, DP Walsh Spatial statistics 20, 206-220, 2017 | 52 | 2017 |
| The Bayesian group lasso for confounded spatial data TJ Hefley, MB Hooten, EM Hanks, RE Russell, DP Walsh Journal of Agricultural, Biological and Environmental Statistics 22, 42-59, 2017 | 48 | 2017 |
| Temporal variation and scale in movement-based resource selection functions MB Hooten, EM Hanks, DS Johnson, MW Alldredge Statistical Methodology 17, 82-98, 2014 | 48 | 2014 |
| Confronting models with data: the challenges of estimating disease spillover PC Cross, DJ Prosser, AM Ramey, EM Hanks, KM Pepin Philosophical Transactions of the Royal Society B 374 (1782), 20180435, 2019 | 46 | 2019 |
| Reconciling multiple data sources to improve accuracy of large‐scale prediction of forest disease incidence EM Hanks, MB Hooten, FA Baker Ecological applications 21 (4), 1173-1188, 2011 | 44 | 2011 |
| Time-varying predatory behavior is primary predictor of fine-scale movement of wildland-urban cougars FE Buderman, MB Hooten, MW Alldredge, EM Hanks, JS Ivan Movement Ecology 6, 1-16, 2018 | 34 | 2018 |
| Optimal SARS-CoV-2 vaccine allocation using real-time attack-rate estimates in Rhode Island and Massachusetts TNA Tran, NB Wikle, E Albert, H Inam, E Strong, K Brinda, SM Leighow, ... BMC medicine 19, 1-14, 2021 | 33 | 2021 |
Mevin HootenProfessor, The University of Texas at AustinVerified email at austin.utexas.edu