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Spatio-temporal causal inference based on point process data. You provide the raw data of locations and timings of treatment and outcome events, specify counterfactual scenarios, and the package estimates causal effects over specified spatial and temporal windows. See Papadogeorgou, et al. (2022) <doi:10.1111/rssb.12548>.
Version: | 0.3.2 |
Depends: | R (≥ 3.5.0) |
Imports: | data.table, dplyr, furrr, ggplot2, ggpubr, latex2exp, mclust, progressr, purrr, sf, spatstat.explore, spatstat.geom, spatstat.model, spatstat.univar, terra, tidyr, tidyselect, tidyterra |
Suggests: | elevatr, geosphere, gridExtra, ggthemes, knitr, readr |
Published: | 2024-07-19 |
DOI: | 10.32614/CRAN.package.geocausal |
Author: | Mitsuru Mukaigawara
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Maintainer: | Mitsuru Mukaigawara <mitsuru_mukaigawara at g.harvard.edu> |
License: | MIT + file LICENSE |
URL: | https://github.com/mmukaigawara/geocausal |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | geocausal results |
Reference manual: | geocausal.pdf |
Package source: | geocausal_0.3.2.tar.gz |
Windows binaries: | r-devel: geocausal_0.3.2.zip, r-release: geocausal_0.3.2.zip, r-oldrel: geocausal_0.3.2.zip |
macOS binaries: | r-release (arm64): geocausal_0.3.2.tgz, r-oldrel (arm64): geocausal_0.3.2.tgz, r-release (x86_64): geocausal_0.3.2.tgz, r-oldrel (x86_64): geocausal_0.3.2.tgz |
Old sources: | geocausal archive |
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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.
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