abstract for Psychoco 2026

vignettes/Psychoco2026/abstract.md

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+tinyplot: Lightweight Extension of the Base R Graphics System
+
+Grant McDermott, Vincent Arel-Bundock, Achim Zeileis
+
+The base R graphics system provides a lot of powerful infrastructure for drawing
+data visualizations. At the core is the `plot()` generic function with its
+default and formula methods. The default method can handle many basic plotting
+elements (points, lines, etc.) and the formula method flexibly handles various
+`y ~ x` setups including scatterplots (numeric `y` vs. numeric `x`), boxplots
+(numeric `y` vs. categorical `x`), and spineplots/spinograms (categorical `y`).
+Moreover, there are many elements that can be added like legends, axes,
+annotation, grids of displays, etc.
+
+However, based on this powerful infrastructure base R provides only rather
+limited convenience features such as those pioneered by newer (`grid`-based)
+visualization packages like `ggplot2` and `lattice`, e.g., grouped plots with
+automatic legends and/or facets, advanced visualization types, and easy
+customization via ready-made themes.
+
+The `tinyplot` package fills this gap by providing a lightweight extension of
+the base R graphics system. It aims to preserve the strengths of the base R
+infrastructure (including the formula-based interface) while adding the
+convenience features above without requiring (strong) non-base dependencies.
+The presentation provides an introduction to `tinyplot` using various
+visualization examples, highlighting strengths and weaknesses compared to other
+packages. The package is available from CRAN
+(<https://doi.org/10.32614/CRAN.package.tinyplot>) and has many more galleries
+and tutorials at <https://grantmcdermott.com/tinyplot/>.