Click here to go to my github page.
- Holthuijzen, Maike, et al. 2024. "Synthesizing data products, mathematical models, and observational measurements for lake temperature forecasting" (in preparation).
- Holthuijzen, Maike, et al. 2023. "Novel application of a process convolution model approach for calibrating output from numerical models". Environmetrics. http://doi.org/10.1002/env.2822
- Higdon, Dave and Holthuijzen, Maike. "Multivariate and functional output emulation ". The Handbook of Statistical Methods for Computer Modeling. (in review)
- Holthuijzen, Maike, et al. "Robust bias-correction of precipitation extremes using a novel hybrid empirical quantile-mapping method." Theoretical and Applied Climatology (2022): 1-20. Link: https://link.springer.com/article/10.1007/s00704-022-04035-2
- Holthuijzen, M. F., Beckage, B., Clemins, P. J., Higdon, D., & Winter, J. M. (2021). "Constructing High-Resolution, Bias-Corrected Climate Products: A Comparison of Methods". Journal of Applied Meteorology and Climatology, 60(4), 455-475. Link: https://journals.ametsoc.org/view/journals/apme/60/4/JAMC-D-20-0252.1.xml
- Holthuijzen, Maike F., and Kari E. Veblen. "Grazing effects on precipitation-driven associations between sagebrush and perennial grasses." Western North American Naturalist 76.3 (2016): 313-325. Link: journals.plos.org/plosone/article?id=10.1371/journal.pone.0143170 :
- Holthuijzen, Maike F., and Kari E. Veblen. "Grass-shrub associations over a precipitation gradient and their implications for restoration in the Great Basin, USA." PloS one 10.12 (2015): e0143170. Link: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0143170
- Link to my MS statistics thesis "A Comparison of Five Statistical Methods for Predicting Stream Temperature across Stream Networks" : digitalcommons.usu.edu/cgi/viewcontent.cgi?article=7750&context=etd