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Render a pairwise, asymmetric smoothed-association matrix of continuous variables. Each cell shows the fitted spline from an 'mgcv' generalised additive model, with the upper triangle displaying 'gam(x_j ~ s(x_i))' and the lower triangle 'gam(x_i ~ s(x_j))'. Unlike Pearson's correlation matrix, the visualisation is intentionally asymmetric, revealing heteroscedasticity, leverage, and directional non-linearity that a single scalar correlation hides. An asymmetry index and a 24-category shape taxonomy quantify the directional difference and qualitative form of each fitted smooth.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.3.0) |
| Imports: | mgcv (≥ 1.9.0), ggplot2 (≥ 3.5.0), patchwork (≥ 1.1.0), grid, stats, cli (≥ 3.6.0), lifecycle, rlang (≥ 1.1.0) |
| Suggests: | agridat, future, future.apply, knitr, MASS, palmerpenguins, rmarkdown, testthat (≥ 3.0.0), vdiffr (≥ 1.0.0), withr |
| Published: | 2026-04-28 |
| DOI: | 10.32614/CRAN.package.janusplot |
| Author: | Max Moldovan |
| Maintainer: | Max Moldovan <max.moldovan at adelaide.edu.au> |
| BugReports: | https://github.com/max578/janusplot/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/max578/janusplot, https://max578.github.io/janusplot/ |
| NeedsCompilation: | no |
| Language: | en-AU |
| Citation: | janusplot citation info |
| Materials: | README, NEWS |
| CRAN checks: | janusplot results |
| Reference manual: | janusplot.html , janusplot.pdf |
| Vignettes: |
Asymmetric Smoothed-Association Matrices (source, R code) Shape-recognition sensitivity study (source, R code) |
| Package source: | janusplot_0.1.0.tar.gz |
| Windows binaries: | r-devel: janusplot_0.1.0.zip, r-release: janusplot_0.1.0.zip, r-oldrel: janusplot_0.1.0.zip |
| macOS binaries: | r-release (arm64): janusplot_0.1.0.tgz, r-oldrel (arm64): janusplot_0.1.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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