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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
DOI:10.32614/CRAN.package.surveyCV
Author:Cole Guerin [aut], Thomas McMahon [aut], Jerzy WieczorekORCID 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.html ,surveyCV.pdf
Vignettes:intro (source,R code)
plots-for-Stat-paper (source,R code)
test-Auto (source,R code)

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, r-oldrel (x86_64):surveyCV_0.2.0.tgz
Old sources: surveyCV archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=surveyCVto link to this page.


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