Package: bayesiansurpriser
Title: Bayesian Surprise for De-Biasing Thematic Maps
Version: 0.1.0
Authors@R: 
    person("Dmitry", "Shkolnik", , "shkolnikd@gmail.com", role = c("aut", "cre"))
Author: Dmitry Shkolnik [aut, cre]
Maintainer: Dmitry Shkolnik <shkolnikd@gmail.com>
Description: 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.
License: MIT + file LICENSE
URL: https://dshkol.github.io/bayesiansurpriser/,
        https://github.com/dshkol/bayesiansurpriser
BugReports: https://github.com/dshkol/bayesiansurpriser/issues
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
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
Config/testthat/edition: 3
VignetteBuilder: knitr
LazyData: true
Config/pak/sysreqs: libabsl-dev cmake libgdal-dev gdal-bin libgeos-dev
        libssl-dev libproj-dev libsqlite3-dev libudunits2-dev
Repository: https://dshkol.r-universe.dev
Date/Publication: 2026-04-21 06:44:20 UTC
RemoteUrl: https://github.com/dshkol/bayesiansurpriser
RemoteRef: HEAD
RemoteSha: 83e5f8b06e55a39c93e622582c5be8d57c5680c6
NeedsCompilation: no
Packaged: 2026-06-21 08:38:47 UTC; root