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 [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-prerel: surveyCV_0.2.0.zip, r-release: surveyCV_0.2.0.zip, r-oldrel: surveyCV_0.2.0.zip
macOS binaries:	r-prerel (arm64): surveyCV_0.2.0.tgz, r-release (arm64): surveyCV_0.2.0.tgz, r-oldrel (arm64): surveyCV_0.2.0.tgz, r-prerel (x86_64): surveyCV_0.2.0.tgz, r-release (x86_64): surveyCV_0.2.0.tgz
Old sources:	surveyCV archive

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