smartcor: Automatic Correlation Method Selection Based on Variable Types

Detects variable types (continuous, count, binary, ordinal, categorical) and selects the appropriate correlation method for each pair. Supports Pearson, Spearman, Kendall's tau, point-biserial, rank-biserial, phi, tetrachoric, polychoric, polyserial, Cramer's V, Tschuprow's T, Theil's U, Yule's Q, and Goodman-Kruskal's gamma, each with a confidence interval and p-value. Explains the selection rationale in the output, follows tidy data principles, and works in both interactive and scripted workflows. The methodology is described in Harshvardhan and Ranjan (2026) <doi:10.48550/arXiv.2607.22285>.

Version: 1.0.1
Depends: R (≥ 3.6.0)
Imports: cli (≥ 3.0.0), generics, ggplot2 (≥ 3.4.0), graphics, grDevices, mvtnorm, polycor, rlang (≥ 1.0.0), stats, tibble, utils, withr
Suggests: knitr, MASS, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-08-09
DOI: 10.32614/CRAN.package.smartcor (may not be active yet)
Author: M. Harshvardhan [aut, cre, cph], Pritam Ranjan [aut, cph]
Maintainer: M. Harshvardhan <harshvardhan at aus.edu>
BugReports: https://github.com/harshvardhaniimi/smartcor/issues
License: GPL (≥ 3)
URL: https://harshvardhaniimi.github.io/smartcor/, https://github.com/harshvardhaniimi/smartcor
NeedsCompilation: no
Citation: smartcor citation info
Materials: README, NEWS
CRAN checks: smartcor results

Documentation:

Reference manual: smartcor.html , smartcor.pdf
Vignettes: Confidence intervals and p-values (source, R code)
Getting Started with smartcor (source, R code)
Choosing the Right Correlation Method: Theory and Rationale (source, R code)

Downloads:

Package source: smartcor_1.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): smartcor_1.0.1.tgz, r-oldrel (arm64): smartcor_1.0.1.tgz, r-release (x86_64): not available, r-oldrel (x86_64): smartcor_1.0.1.tgz

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