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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 |
DOI: | 10.32614/CRAN.package.surveyCV |
Author: | Cole Guerin [aut], Thomas McMahon [aut], Jerzy Wieczorek [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 |
Reference manual: | surveyCV.pdf |
Vignettes: |
intro plots-for-Stat-paper test-Auto |
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, r-oldrel (x86_64): surveyCV_0.2.0.tgz |
Old sources: | surveyCV archive |
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These binaries (installable software) and packages are in development.
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