surveyCV: Cross Validation Based on Survey Design

Functions to generate test error estimates using cross validation, based on how a survey design is 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 draft paper on "K-Fold Cross-Validation for Complex Sample Surveys" (under review; a copy is in the 'data-raw' folder of our GitHub repo) explains why differing how we take folds based on survey design is useful.

Version: 0.1.1
Depends: R (≥ 4.0)
Imports: survey (≥ 4.1), magrittr (≥ 2.0)
Suggests: dplyr (≥ 1.0), ggplot2 (≥ 3.3), gridExtra (≥ 2.3), ISLR (≥ 1.2), knitr (≥ 1.29), rmarkdown (≥ 2.2), testthat (≥ 3.1), grid (≥ 4.0), splines (≥ 4.0)
Published: 2022-01-10
Author: Cole Guerin [aut], Thomas McMahon [aut], Jerzy Wieczorek [cre, aut], Hunter Ratliff [ctb]
Maintainer: Jerzy Wieczorek <jawieczo at>
License: GPL-2 | GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: surveyCV results


Reference manual: surveyCV.pdf
Vignettes: intro


Package source: surveyCV_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): surveyCV_0.1.1.tgz, r-release (x86_64): surveyCV_0.1.1.tgz, r-oldrel: surveyCV_0.1.1.tgz


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