Recent News:

  • New paper on fast multi-stage computing:

Johnson, D.S., B.M. Brost, and M.B. Hooten. (2022). Greater than the sum of its parts: Computationally flexible Bayesian hierarchical modeling. Journal of Agricultural, Biological, and Environmental Statistics, 27: 382-400.

  • New paper accepted on landscape genetics:

Zimmerman, S., C. Aldridge, S. Oyler-McCance, and M.B. Hooten. (In Press). Scale-dependent influence of the sagebrush community on genetic connectivity of the sagebrush obligate Gunnison sage-grouse. Molecular Ecology.

  • New paper accepted on environments that are robust to climate change:

Raiho, A., H.R. Scharf, C.A. Roland, D.K. Swanson, S.E. Stehn, and M.B. Hooten. (In Press). Searching for refuge: A framework for identifying site factors conferring resistance to climate-driven vegetation change. Diversity and Distributions.

  • New paper on multistage computing for optimal design:

Leach, C.B., P.J. Williams, J.M. Eisaguirre, J.N. Womble, M.R. Bower, and M.B. Hooten. (2022). Recursive Bayesian computation facilitates adaptive optimal design in ecological studies. Ecology, 103: e03573.

  • New paper accepted in JABES:

Lu, X., M.B. Hooten, A. Kaplan, J.N. Womble, and M.R. Bower. (In Press). Improving wildlife population inference from aerial imagery data through entity resolution. Journal of Agricultural, Biological, and Environmental Statistics.

  • New paper accepted in ISR:

Scharf, H.R., X. Lu, P.J. Williams, and M.B. Hooten. (In Press). Constructing flexible, identifiable, and interpretable statistical models for binary data. International Statistical Review.

  • New paper on inverse reinforcement learning accepted in Annals of Applied Statistics:

Schafer, T.L.J., C.K. Wikle, and M.B. Hooten. (In Press). Bayesian inverse reinforcement learning for collective animal movement. Annals of Applied Statistics.