Package: surveyCV
Type: Package
Title: Cross Validation Based on Survey Design
Version: 0.2.0
Date: 2022-03-14
Authors@R: c(
    person("Cole", "Guerin", email = "cole@guerincreative.com", role = "aut"),
    person("Thomas", "McMahon", email = "thomasmcmahon9@gmail.com", role = "aut"),
    person("Jerzy", "Wieczorek", email = "jawieczo@colby.edu", role = c("cre", "aut"),
           comment = c(ORCID = "0000-0002-2859-6534")),
    person("Hunter", "Ratliff", role = "ctb"))
Description: 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.
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: TRUE
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)
VignetteBuilder: knitr
URL: https://github.com/ColbyStatSvyRsch/surveyCV/
BugReports: https://github.com/ColbyStatSvyRsch/surveyCV/issues
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2022-03-15 02:52:15 UTC; jawieczo
Author: Cole Guerin [aut],
  Thomas McMahon [aut],
  Jerzy Wieczorek [cre, aut] (<https://orcid.org/0000-0002-2859-6534>),
  Hunter Ratliff [ctb]
Maintainer: Jerzy Wieczorek <jawieczo@colby.edu>
Repository: CRAN
Date/Publication: 2022-03-15 08:50:02 UTC
Built: R 4.6.0; ; 2026-04-28 12:01:34 UTC; unix
