When to use CorSym | Simulated example: extreme ordering | Simulated example: partial orderings
Package: corsym 1.0.1
Alejandro Ochoa
corsym: Correlation Estimation for Exchangeable/Symmetrical Variables
We implement a new correlation estimator, CorSym, designed for exchangeable variables, where the ordering of the two values in the pair is arbitrary. This kind of data arises frequently in the study of assortative pairing (for example, income in a couple). The standard Pearson estimator is sensitive to such ordering and can be highly biased when the order is biased (when the first value tends to have lower or higher values than the second value). CorSym gives the same estimate deterministically for all orders within each pair, and estimates the desired correlation without bias (variables must be exchangeable). The package also includes utilities to simulate biased orders and test for order bias. Described in Kennedy and Ochoa (2026) <doi:10.64898/2026.08.22.746446>.
Authors:
corsym_1.0.1.tar.gz
corsym_1.0.1.zip(r-4.7-any)corsym_1.0.1.zip(r-4.6-any)corsym_1.0.1.zip(r-4.5-any)
corsym_1.0.1.tgz(r-4.6-any)corsym_1.0.1.tgz(r-4.5-any)
corsym_1.0.1.tar.gz(r-4.7-any)corsym_1.0.1.tar.gz(r-4.6-any)
corsym_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
corsym/json (API)
| # Install 'corsym' in R: |
| install.packages('corsym', repos = c('https://ochoalab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ochoalab/corsym/issues
Last updated from:74b492bfeb. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 121 | ||
| source / vignettes | OK | 208 | ||
| linux-release | OK | 118 | ||
| macos-release | OK | 92 | ||
| macos-oldrel | OK | 77 | ||
| windows-devel | OK | 67 | ||
| windows-release | OK | 73 | ||
| windows-oldrel | OK | 73 | ||
| wasm-release | OK | 100 |
Exports:add_cor_CIcorsymorder_bias_testpartial_orderpearsonrandomize_order
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Calculate confidence intervals (CIs) for correlation estimates | add_cor_CI |
| Calculate CorSym estimates with confidence intervals (CIs) | corsym |
| Test for order bias | order_bias_test |
| Apply partial ordering to the rows of a matrix | partial_order |
| Calculate Pearson estimates with confidence intervals (CIs) | pearson |
| Randomize ordering of each row of a matrix | randomize_order |
