Trevor Hefley

Associate Professor

Department of Statistics

Kansas State University

Welcome to my research website! Broadly, my research focuses on developing and applying spatio-temporal statistical methods to inform environmental decisions.

Recent News

  • July 2021: New paper accepted in Ecology that demonstrates how to embed machine learning algorithms into Bayesian occupancy models that account for spatial autocorrelation. .

    • Mohankumar, N.M., and T.J. Hefley. (in press) Using machine learning to identify nontraditional spatial dependence in occupancy data. Ecology.

  • July 2021: New paper accepted in Crop Science that documents the impact of tillers on yield in corn.

    • Veenstra, R.L., C. Messina, D. Berning, L. Haag, P. Carter, T. Hefley, V. Prasad I. Ciampitti. (in press) Effect of tillers on corn yield: Exploring trait plasticity potential in unpredictable environments. Crop Science [pdf]

  • June 2021: New paper accepted in Plant Methods that reviews, explains and demonstrates different parameter estimation techniques for the light extinction coefficient.

    • Lacasa, J., T.J. Hefley, F. Curin, M.E Otegui, I.A. Ciampitti. (in press) A practical guide to estimating the light extinction coefficient with nonlinear models – an example in maize. Plant Methods [pdf]

  • May 2021: New paper accepted in Spatial Statistics that shows how to recover individual-level inference from aggregated binary data.

    • Walker, N.B., T.J. Hefley, A.E. Ballmann, R.E. Russell, D.P. Walsh. (in press) Recovering individual-level spatial inference from aggregated binary data. Spatial Statistics [pdf]

  • May 2021: New paper accepted in Agricultural Systems Journal that reviews and compares regression approaches to evaluate predictions from crop models.

    • Correndo, A.A., T.J. Hefley, D. Holzworth, D., I.A. Ciampitti. (in press) Revisiting linear regression to test agreement in continuous predicted-observed datasets. Agricultural Systems Journal [pdf]