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 Prediction Telemetry Spatial Data Model Movement Animal Sampling Effect Autocorrelation Connectivity Resource Selection Continuous Time Generalized Linear Mixed Model Single Nucleotide Polymorphism Machine Learning Physiology Geostatistics Bayesian Analysis Modeling Ecosystem Model Based Communicable Diseases Infectious Diseases Statistical Models

Most Recent Papers

Optimal SARS-CoV-2 vaccine allocation using real-time attack-rate estimates in Rhode Island and Massachusetts

Thu Nguyen Anh Tran, Nathan B. Wikle, Emmy Albert, Haider Inam, Emily Strong, Karel Brinda, Scott M. Leighow, Fuhan Yang, Sajid Hossain, Justin R. Pritchard, Philip Chan, William P. Hanage, Ephraim M. Hanks, Maciej F. Boni, 2021, BMC Medicine

Social fluidity mobilizes contagion in human and animal populations

Ewan Colman, Vittoria Colizza, Ephraim M. Hanks, David P. Hughes, Shweta Bansal, 2021, eLife

A Sample Covariance-Based Approach For Spatial Binary Data

Sahar Zarmehri, Ephraim M. Hanks, Lin Lin, 2021, Journal of Agricultural, Biological, and Environmental Statistics

A novel quantitative framework for riverscape genetics

Shannon L. White, Ephraim M. Hanks, Tyler Wagner, 2020, Ecological Applications

A lattice and random intermediate point sampling design for animal movement

Elizabeth Eisenhauer, Ephraim Hanks, 2020, Environmetrics

Ecological prediction at macroscales using big data: Does sampling design matter?

Patricia A. Soranno, Kendra Spence Cheruvelil, Boyang Liu, Qi Wang, Pang Ning Tan, Jiayu Zhou, Katelyn B.S. King, Ian M. McCullough, Jemma Stachelek, Meridith Bartley, Christopher T. Filstrup, Ephraim M. Hanks, Jean François Lapierre, Noah R. Lottig, Erin M. Schliep, Tyler Wagner, Katherine E. Webster, 2020, Ecological Applications

Machine learning for modeling animal movement

Dhanushi A. Wijeyakulasuriya, Elizabeth W. Eisenhauer, Benjamin A. Shaby, Ephraim M. Hanks, 2020, PLoS One

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

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

Tyler Wagner, Noah R. Lottig, Meridith L. Bartley, Ephraim M. Hanks, Erin M. Schliep, Nathan B. Wikle, Katelyn B.S. King, Ian McCullough, Jemma Stachelek, Kendra S. Cheruvelil, Christopher T. Filstrup, Jean Francois Lapierre, Boyang Liu, Patricia A. Soranno, Pang Ning Tan, Qi Wang, Katherine Webster, Jiayu Zhou, 2020, Limnology And Oceanography Letters on p. 228-235

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, 2020, Global Change Biology on p. 523-538

Most-Cited Papers

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

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

Hierarchical animal movement models for population-level inference

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

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

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

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

Temporal variation and scale in movement-based resource selection functions

M. B. Hooten, E. M. Hanks, D. S. Johnson, M. W. Alldredge, 2014, Statistical Methodology on p. 82-98

On the relationship between conditional (CAR) and simultaneous (SAR) autoregressive models

Jay M. Ver Hoef, Ephraim M. Hanks, Mevin B. Hooten, 2018, Spatial Statistics on p. 68-85

Dynamic spatio-temporal models for spatial data

Trevor J. Hefley, Mevin B. Hooten, Ephraim M. Hanks, Robin E. Russell, Daniel P. Walsh, 2017, Spatial Statistics on p. 206-220