Matt Higham studies spatial statistics with ecological applications. His focus is spatial prediction models with imperfect detection of animals in surveys. He is an Assistant Professor at St. Lawrence University and earned a PhD degree in Statistics from Oregon State University in 2019 and B.S. degrees in Statistics and Botany from Miami University in 2014.
Recent Scholarly Work
- Ver Hoef, J., Johnson, D., Angliss, R., & Higham, M. (2021). Species density models from opportunistic citizen science data. Methods in Ecology and Evolution.
- Higham, M., Ver Hoef, J., Madsen, L., & Aderman, A. (2021). Adjusting a finite population block kriging estimator for imperfect detection. Environmetrics, 32(1), e2654.
- Higham, M., Ver Hoef, J., Frank, B. & Dumelle, M. (Version 0.1.0 Accepted to CRAN 2020, Version 1.0.0 Accepted to CRAN 2021).
sptotal: Predicting Totals and Weighted Sums from Spatial Data.
Please see my GitHub site for other work.
At St. Lawrence University, I have taught Introduction to Statistics, Regression Modeling, Data Science, and co-taught a senior year seminar on data visualization.
In my free time, I enjoy playing racket sports 🎾, jogging 🏃, gaming 🎮, hiking ⛰, and backpacking 🎒!