Why Pearson is not enough | Quick start | Non-linear detection | Asymmetry — a heteroscedastic example | Partial smooths (controlling for covariates) | Changing the palette | Handling missing data | Scaling up — order = "hclust" | Programmatic access — janusplot_data() | Shape metrics explained | Derivative views: theoretical justification and applied use | What derivatives reveal that the fit hides | Estimation — the LP matrix | Noise amplification and why we cap at $k = 2$ | Applied use: gain estimation and dose--response | References cited in this section | Limitations | Citation
This package is hidden from search results because it is not hosted in the universe of the upstream owner
cran. To fix this you can add URL: https://cran.r-universe.dev/janusplot to the package DESCRIPTION file. See also theR-universe documentation.Package: janusplot 0.1.1
Max Moldovan
janusplot: Asymmetric Smoothed-Association Matrices via GAM Fits
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.
Authors:
janusplot_0.1.1.tar.gz
janusplot_0.1.1.tar.gz(r-4.7-any)janusplot_0.1.1.tar.gz(r-4.6-any)
janusplot_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
janusplot/json (API)
| # Install 'janusplot' in R: |
| install.packages('janusplot', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/max578/janusplot/issues
Pkgdown/docs site:https://max578.github.io
Datasets:
- shape_sensitivity_demo - Precomputed shape-recognition sensitivity results
Last updated from:4591e5294b. Checks:4 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 165 | ||
| source / vignettes | OK | 265 | ||
| linux-release-x86_64 | OK | 163 | ||
| wasm-release | OK | 136 |
Exports:janusplotjanusplot_datajanusplot_shape_cutoffsjanusplot_shape_hierarchyjanusplot_shape_metricsjanusplot_shape_sensitivityjanusplot_shape_sensitivity_plotjanusplot_shape_sensitivity_shapesjanusplot_shape_sensitivity_summary
Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglatticelifecycleMatrixmgcvnlmepatchworkR6RColorBrewerrlangS7scalesvctrsviridisLitewithr
Asymmetric Smoothed-Association Matrices
Last update: 2026-07-02
Started: 2026-04-28
Shape-recognition sensitivity study
Design | Pre-registered hypotheses | Precomputed demo | Recovery curves (headline figure) | Archetype confusion | Archetype-level accuracy grid | Numerical summary | Running your own sweep | Custom shape subsets + cutoffs | References
Last update: 2026-04-28
Started: 2026-04-28
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Asymmetric smoothed-association matrix | janusplot |
| Raw GAM fits and per-cell metrics for a smoothed-association matrix | janusplot_data |
| Default cutoff thresholds for 'shape_category' classification | janusplot_shape_cutoffs |
| Shape-category taxonomy table | janusplot_shape_hierarchy |
| Shape metrics for a fitted univariate smooth | janusplot_shape_metrics |
| Shape-recognition sensitivity study | janusplot_shape_sensitivity |
| Visualise a shape-sensitivity sweep | janusplot_shape_sensitivity_plot |
| Canonical ground-truth shapes for the sensitivity study | janusplot_shape_sensitivity_shapes |
| Summarise a shape-sensitivity sweep | janusplot_shape_sensitivity_summary |
| Precomputed shape-recognition sensitivity results (demo) | shape_sensitivity_demo |