Installation
About
Functions to generate K-fold cross validation (CV) folds and CV test error estimates that take into account how a survey dataset's sampling design was constructed (SRS, clustering, stratification, and/or unequal sampling weights). You can input linear and logistic regression models, along with data and a type of survey design in order to get an output that can help you determine which model best fits the data using K-fold cross validation. Our paper on "K-Fold Cross-Validation for Complex Sample Surveys" by Wieczorek, Guerin, and McMahon (2022) doi:10.1002/sta4.454 explains why differing how we take folds based on survey design is useful.
github.com/ColbyStatSvyRsch/surveyCV/ | |
Bug report | File report |
Key Metrics
Downloads
Yesterday | 6 0% |
Last 7 days | 62 +32% |
Last 30 days | 189 -2% |
Last 90 days | 522 -23% |
Last 365 days | 2.256 +1% |