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.

Version: 0.2.0
Depends: R (≥ 4.0)
Imports: survey (≥ 4.1), magrittr (≥ 2.0)
Suggests: dplyr (≥ 1.0), ggplot2 (≥ 3.3), grid (≥ 4.0), gridExtra (≥ 2.3), ISLR (≥ 1.2), knitr (≥ 1.29), rmarkdown (≥ 2.2), rpms (≥ 0.5), splines (≥ 4.0), testthat (≥ 3.1)
Published: 2022-03-15
Author: Cole Guerin [aut], Thomas McMahon [aut], Jerzy Wieczorek ORCID iD [cre, aut], Hunter Ratliff [ctb]
Maintainer: Jerzy Wieczorek <jawieczo at colby.edu>
BugReports: https://github.com/ColbyStatSvyRsch/surveyCV/issues
License: GPL-2 | GPL-3
URL: https://github.com/ColbyStatSvyRsch/surveyCV/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: surveyCV results

Documentation:

Reference manual: surveyCV.pdf
Vignettes: intro
plots-for-Stat-paper
test-Auto

Downloads:

Package source: surveyCV_0.2.0.tar.gz
Windows binaries: r-devel: surveyCV_0.2.0.zip, r-release: surveyCV_0.2.0.zip, r-oldrel: surveyCV_0.2.0.zip
macOS binaries: r-release (arm64): surveyCV_0.2.0.tgz, r-oldrel (arm64): surveyCV_0.2.0.tgz, r-release (x86_64): surveyCV_0.2.0.tgz
Old sources: surveyCV archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=surveyCV to link to this page.