surveyCV - Cross Validation Based on Survey Design
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.
