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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=surveyCV to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4