Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019)
Tables are presented listing parameters used in logistic regression equations describing drought streamflow probabilities in the Northeastern United States. Streamflow daily data, streamflow monthly mean data, maximum likelihood logistic regression (MLLR) equation explanatory parameters, equation goodness of fit parameters, and Receiver Operating Characteristic (ROC) AUC values identifying the utility of each relation, describe each model of the probability (chance) of a particular streamflow daily value exceeding or not exceeding an identified drought streamflow threshold. These models are key inputs to drought forecasting web applications for the northeastern United states {https://usgs.maps.arcgis.com/apps/MapSeries/index.html?appid=b8c5da617a0e4d628e3e39f7dbd512da}
Complete Metadata
| bureauCode |
[ "010:12" ] |
|---|---|
| identifier | http://datainventory.doi.gov/id/dataset/USGS_5d681d5de4b0c4f70cf15c9b |
| spatial | -84.067382812719, 35.977652111331, -66.137695313435, 47.768574328315 |
| theme |
[ "geospatial" ] |
