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bayesiansurpriser: Bayesian Surprise for De-Biasing Thematic Maps

Implements Bayesian Surprise methodology for data visualization, based on Correll and Heer (2017) <doi:10.1109/TVCG.2016.2598839> "Surprise! Bayesian Weighting for De-Biasing Thematic Maps". Provides tools to weight event data relative to spatio-temporal models, highlighting unexpected patterns while de-biasing against known factors like population density or sampling variation. Integrates seamlessly with 'sf' for spatial data and 'ggplot2' for visualization. Supports temporal/streaming data analysis.

Version: 0.1.0
Depends: R (≥ 4.1.0)
Imports: ggplot2 (≥ 3.5.0), sf (≥ 1.0.0), scales (≥ 1.3.0), rlang (≥ 1.1.0), cli, stats, MASS, RColorBrewer
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, dplyr, tibble, vdiffr, tidycensus, tigris, cancensus, ggrepel
Published: 2026-04-21
DOI: 10.32614/CRAN.package.bayesiansurpriser
Author: Dmitry Shkolnik [aut, cre]
Maintainer: Dmitry Shkolnik <shkolnikd at gmail.com>
BugReports: https://github.com/dshkol/bayesiansurpriser/issues
License: MIT + file LICENSE
URL: https://dshkol.github.io/bayesiansurpriser/, https://github.com/dshkol/bayesiansurpriser
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: bayesiansurpriser results

Documentation:

Reference manual: bayesiansurpriser.html , bayesiansurpriser.pdf
Vignettes: Bayesian Surprise with Canadian Census Data (cancensus) (source, R code)
Complete Function Reference with Examples (source, R code)
Visualization with ggplot2 (source, R code)
Introduction to bayesiansurpriser (source, R code)
Understanding Model Types (source, R code)
Spatial Data Workflows with sf (source, R code)
Temporal and Streaming Analysis (source, R code)
Bayesian Surprise with US Census Data (tidycensus) (source, R code)

Downloads:

Package source: bayesiansurpriser_0.1.0.tar.gz
Windows binaries: r-release: bayesiansurpriser_0.1.0.zip, r-oldrel: bayesiansurpriser_0.1.0.zip
macOS binaries: r-release (arm64): bayesiansurpriser_0.1.0.tgz, r-oldrel (arm64): bayesiansurpriser_0.1.0.tgz, r-release (x86_64): bayesiansurpriser_0.1.0.tgz, r-oldrel (x86_64): bayesiansurpriser_0.1.0.tgz

Linking:

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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.