1 citations · 1 across the 4 of their papers we have counts for
4 papers
Unsupervised anomaly detection in spatio-temporal stream network sensor data
Edgar Santos-Fernandez, Jay M. Ver Hoef, Erin E. Peterson +6
The use of in-situ digital sensors for water quality monitoring is becoming increasingly common worldwide. While these sensors provide near real-time data for science, the data are…
SSNdesign -- an R package for pseudo-Bayesian optimal and adaptive sampling designs on stream networks
Alan R. Pearse, James M. McGree, Nicholas A. Som +4
Streams and rivers are biodiverse and provide valuable ecosystem services. Maintaining these ecosystems is an important task, so organisations often monitor the status and trends i…
Comparing Spatial Regression to Random Forests for Large Environmental Data Sets
Eric W. Fox, Jay M. Ver Hoef, Anthony R. Olsen
Environmental data may be "large" due to number of records, number of covariates, or both. Random forests has a reputation for good predictive performance when using many covariate…
On the Relationship between Conditional (CAR) and Simultaneous (SAR) Autoregressive Models
Jay M. Ver Hoef, Ephraim M. Hanks, Mevin B. Hooten
We clarify relationships between conditional (CAR) and simultaneous (SAR) autoregressive models. We review the literature on this topic and find that it is mostly incomplete. Our m…