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.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.1.1 by Jerzy Wieczorek, 9 days ago

Report a bug at

Browse source code at

Authors: Cole Guerin [aut] , Thomas McMahon [aut] , Jerzy Wieczorek [cre, aut] , Hunter Ratliff [ctb]

Documentation:   PDF Manual  

GPL-2 | GPL-3 license

Imports survey, magrittr

Suggests dplyr, ggplot2, gridExtra, ISLR, knitr, rmarkdown, testthat, grid, splines

See at CRAN