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Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019)

Dates

Publication Date
Start Date
1884-01-01
End Date
2018-10-31

Citation

Austin, S.H., 2021, Terms, Statistics, and Performance Measures for Maximum Likelihood Logistic Regression Models Estimating Hydrological Drought Probabilities in the Northeastern United States (2019): U.S. Geological Survey data release, https://doi.org/10.5066/P9E3SK56.

Summary

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.

Contacts

Point of Contact :
Samuel H Austin
Process Contact :
Samuel H Austin
Originator :
Samuel H Austin
Metadata Contact :
Samuel H Austin
Publisher :
U.S. Geological Survey, U.S. Geological Survey
Distributor :
U.S. Geological Survey - ScienceBase
SDC Data Owner :
Virginia and West Virginia Water Science Center
USGS Mission Area :
Water Resources

Attached Files

Click on title to download individual files attached to this item.

Austin-DATAFILE_1_Northeast_MLLR_Parameter_and_ROC_Estimates.csv
“Austin-DATAFILE_1_Northeast_MLLR Study”
8.83 MB text/csv
Austin-DATAFILE_2_Northeast_MLLR_Study_Data_NWIS accessed 2018-12-03.csv
“Austin-DATAFILE_2_Northeast_MLLR Study”
698.35 MB text/csv

Purpose

The data were obtained and developed to identify and describe terms used in maximum likelihood logistic regression (MLLR) models estimating streamflow drought probabilities at selected USGS gaged basins in the northeastern United States.

Additional Information

Identifiers

Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P9E3SK56

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