Bayesian Surprise for De-Biasing Thematic Maps [R package bayesiansurpriser version 0.1.0]

Dmitry Shkolnik

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 (may not be active yet)
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-devel: not available, 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): not available, r-release (x86_64): bayesiansurpriser_0.1.0.tgz, r-oldrel (x86_64): bayesiansurpriser_0.1.0.tgz

Linking:

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