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CausalImpact: Inferring Causal Effects using Bayesian Structural Time-SeriesModels

Implements a Bayesian approach to causal impact estimation in time series, as described in Brodersen et al. (2015) <doi:10.1214/14-AOAS788>. See the package documentation on GitHub <https://google.github.io/CausalImpact/> to get started.

Version:1.4.1
Depends:bsts (≥ 0.9.0)
Imports:assertthat (≥ 0.2.0),Boom,ggplot2,zoo
Suggests:covr,knitr,rmarkdown,testthat,vdiffr
Published:2025-09-26
DOI:10.32614/CRAN.package.CausalImpact
Author:Kay H. Brodersen [aut], Alain Hauser [aut, cre]
Maintainer:Alain Hauser <alhauser at google.com>
License:Apache License 2.0 | fileLICENSE
Copyright:Copyright (C) 2014-2025 Google, Inc.
URL:https://google.github.io/CausalImpact/
NeedsCompilation:no
Citation:CausalImpact citation info
Materials:README
In views:Bayesian,CausalInference
CRAN checks:CausalImpact results

Documentation:

Reference manual:CausalImpact.html ,CausalImpact.pdf
Vignettes:CausalImpact (source,R code)

Downloads:

Package source: CausalImpact_1.4.1.tar.gz
Windows binaries: r-devel:CausalImpact_1.4.1.zip, r-release:CausalImpact_1.4.1.zip, r-oldrel:CausalImpact_1.4.1.zip
macOS binaries: r-release (arm64):CausalImpact_1.4.1.tgz, r-oldrel (arm64):CausalImpact_1.4.1.tgz, r-release (x86_64):CausalImpact_1.4.1.tgz, r-oldrel (x86_64):CausalImpact_1.4.1.tgz
Old sources: CausalImpact archive

Reverse dependencies:

Reverse imports:MarketMatching,SPORTSCausal

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=CausalImpactto link to this page.


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