Ephraim M. Hanks

Associate Professor of Statistics

Ephraim M. Hanks

Research Summary

Spatio-Temporal Statistics. Bayesian Hierarchical Modeling. Optimal Sampling. Animal Movement. Landscape Genetics.

Huck Affiliations

Publication Tags

Animals Telemetry Modeling Movement Resource Selection Prediction Ants Model Animal Uncertainty Geographic Information Systems Methodology Autocorrelation Connectivity Inference Continuous Time Method Extreme Values Bayesian Analysis Remote Sensing Interaction Geostatistics Individual Based Model Physiology Ecology

Most Recent Papers

Bayesian analysis of spatial generalized linear mixed models with Laplace moving average random fields

Adam Walder, Ephraim M. Hanks, 2020, Computational Statistics and Data Analysis

A lattice and random intermediate point sampling design for animal movement

Elizabeth Eisenhauer, Ephraim Hanks, 2020, Environmetrics on p. e2618

A Dynamic Individual-Based Model for High-Resolution Ant Interactions

Nathan B. Wikle, Ephraim M. Hanks, David P. Hughes, 2019, Journal of Agricultural, Biological, and Environmental Statistics on p. 589-609

Ant colonies maintain social homeostasis in the face of decreased density

Andreas P. Modlmeier, Ewan Colman, Ephraim M. Hanks, Ryan Bringenberg, Shweta Bansal, David P. Hughes, 2019, eLife

Spatially structured statistical network models for landscape genetics

Erin E. Peterson, Ephraim M. Hanks, Mevin B. Hooten, Jay M. Ver Hoef, Marie Josée Fortin, 2019, Ecological Monographs on p. e01355

Extreme value-based methods for modeling elk yearly movements

Dhanushi A. Wijeyakulasuriya, Ephraim Mont Hanks, Benjamin Adam Shaby, Paul C. Cross, 2019, Journal of Agricultural, Biological, and Environmental Statistics on p. 73-91

Effects of two centuries of global environmental variation on phenology and physiology of Arabidopsis thaliana

Victoria L. DeLeo, Duncan N.L. Menge, Ephraim M. Hanks, Thomas E. Juenger, Jesse R. Lasky, 2019, Global Change Biology

Confronting models with data: the challenges of estimating disease spillover

Paul Cross, Diann Prosser, Andrew Ramey, Ephraim Hanks, Kim Pepin, 2019, Philosophical Transactions of the Royal Society B on p. 20180435

Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data

Tyler Wagner, Noah Lottig, Meridith Bartley, Ephraim Hanks, Erin Schliep, Nathan Wikle, Katelyn King, Ian McCullough, Joseph Stachelek, Kendra Cheruvelil, others, 2019, Limnology and Oceanography Letters

Identifying and characterizing extrapolation in multivariate response data

Meridith Bartley, Ephraim Hanks, Erin Schliep, Patricia Soranno, Tyler Wagner, 2019, PloS ONE

Most-Cited Papers

Agent-based inference for animal movement and selection

Mevin B. Hooten, Devin S. Johnson, Ephraim Mont Hanks, John H. Lowry, 2010, Journal of Agricultural, Biological, and Environmental Statistics on p. 523-538

Velocity-Based movement modeling for individual and population level inference

Ephraim M. Hanks, Mevin B. Hooten, Devin S. Johnson, Jeremy T. Sterling, 2011, PloS one on p. e22795

Continuous-time discrete-space models for animal movement

Ephraim M. Hanks, Mevin B. Hooten, Mat W. Alldredge, 2015, Annals of Applied Statistics on p. 145-165

Reconciling resource utilization and resource selection functions

Mevin B. Hooten, Ephraim Mont Hanks, Devin S. Johnson, Mat W. Alldredge, 2013, Journal of Animal Ecology on p. 1146-1154

Circuit theory and model-based inference for landscape connectivity

Ephraim Mont Hanks, Mevin B. Hooten, 2013, Journal of the American Statistical Association on p. 22-33

Spatial autoregressive models for statistical inference from ecological data

Jay M. Ver Hoef, Erin E. Peterson, Mevin B. Hooten, Ephraim M. Hanks, Marie Josèe Fortin, 2018, Ecological Monographs on p. 36-59

Animal movement constraints improve resource selection inference in the presence of telemetry error

Brian M. Brost, Mevin B. Hooten, Ephraim M. Hanks, Robert J. Small, 2015, Ecology on p. 2590-2597

Hierarchical animal movement models for population-level inference

Mevin B. Hooten, Frances E. Buderman, Brian M. Brost, Ephraim Mont Hanks, Jacob S. Ivan, 2016, Environmetrics on p. 322-333

Social, spatial, and temporal organization in a complex insect society

Lauren E. Quevillon, Ephraim M. Hanks, Shweta Bansal, David P. Hughes, 2015, Scientific reports

Reconciling multiple data sources to improve accuracy of large-scale prediction of forest disease incidence

Ephraim Mont Hanks, Mevin B. Hooten, Fred A. Baker, 2011, Ecological Applications on p. 1173-1188