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

Links

Most Recent Publications

A practical guide to understanding and validating complex models using data simjulations

Grace DiRenzo, Ephraim Hanks, D Miller, Methods in Ecology and Evolution on p. 203-217

Impact of a multi-pronged cholera intervention in an endemic setting

Alexandre Blake, Adam Walder, Ephraim M. Hanks, Placide Okitayemba Welo, Francisco Luquero, Didier Bompangue, Nita Bharti, 2025, PLoS Neglected Tropical Diseases

Integrated movement models for individual tracking and species distribution data

Frances E. Buderman, Ephraim M. Hanks, Viviana Ruiz-Gutierrez, Michael Shull, Robert K. Murphy, David A.W. Miller, 2025, Methods in Ecology and Evolution on p. 345-361

A novel methodology for gamma-ray spectra dataset procurement over varying standoff distances and source activities

Aaron P. Fjeldsted, Tyler J. Morrow, Clayton Scott, Yilun Zhu, Darren E. Holland, Ephraim M. Hanks, Azaree T. Lintereur, Douglas Edward Wolfe, 2024, Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

Modeling First Arrival of Migratory Birds Using a Hierarchical Max-Infinitely Divisible Process

Dhanushi A. Wijeyakulasuriya, Ephraim M. Hanks, Benjamin Adam Shaby, 2024, Journal of Agricultural, Biological, and Environmental Statistics

A continuous classification of the 476,697 lakes of the conterminous US based on geographic archetypes

Jean Francois Lapierre, Katherine E. Webster, Ephraim M. Hanks, Tyler Wagner, Patricia A. Soranno, Ian M. McCullough, Kaitlin L. Reinl, Marcella Domka, Noah R. Lotting, 2023, Limnology and Oceanography on p. 2759-2773

A combination of annual and nonannual forces drive respiratory disease in the tropics

Fuhan Yang, Joseph L. Servadio, Nguyen Thi Le Thanh, Ha Minh Lam, Marc Choisy, Pham Quang Thai, Tran Thi Nhu Thao, Nguyen Ha Thao Vy, Huynh Thi Phuong, Tran Dang Nguyen, Dong Thi Hoai Tam, Ephraim M. Hanks, Ha Vinh, Ottar N. Bjornstad, Nguyen Van Vinh Chau, Maciej F. Boni, 2023, BMJ Global Health

A practical guide to understanding and validating complex models using data simulations

Graziella V. DiRenzo, Ephraim Hanks, David A.W. Miller, 2023, Methods in Ecology and Evolution on p. 203-217

SARS-CoV-2 Attack Rate and Population Immunity in Southern New England, March 2020 to May 2021

T Tran, N Wikle, F Yang, H Inam, S Leighow, B Gentilesco, P Chan, E Albert, E Strong, Justin R. Pritchard, W Hanage, Ephraim Hanks, F Crawford, Maciej F. Boni, 2022, JAMA network open on p. e2214171

A Mechanistic Model of Annual Sulfate Concentrations in the United States

Nathan B. Wikle, Ephraim M. Hanks, Lucas R.F. Henneman, Corwin M. Zigler, 2022, Journal of the American Statistical Association on p. 1082-1093

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

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

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

Machine learning for modeling animal movement

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

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

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

Confronting models with data: The challenges of estimating disease spillover

Paul C. Cross, Diann J. Prosser, Andrew M. Ramey, Ephraim M. Hanks, Kim M. Pepin, 2019, Philosophical Transactions of the Royal Society B: Biological Sciences

The Bayesian Group Lasso for Confounded Spatial Data

Trevor J. Hefley, Mevin B. Hooten, Ephraim M. Hanks, Robin E. Russell, Daniel P. Walsh, 2017, Journal of Agricultural, Biological, and Environmental Statistics on p. 42-59