CausalImpact: Inferring Causal Effects using Bayesian Structural Time-Series Models

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: 1.2.3
Depends: bsts (≥ 0.7.0)
Imports: assertthat (≥ 0.2.0), Boom, dplyr, ggplot2, zoo
Suggests: knitr, testthat
Published: 2017-09-14
Author: Kay H. Brodersen, Alain Hauser
Maintainer: Alain Hauser <alhauser at google.com>
License: Apache License 2.0 | file LICENSE
Copyright: Copyright (C) 2014-2017 Google, Inc.
URL: https://google.github.io/CausalImpact/
NeedsCompilation: no
Citation: CausalImpact citation info
Materials: README
CRAN checks: CausalImpact results

Downloads:

Reference manual: CausalImpact.pdf
Vignettes: CausalImpact
Package source: CausalImpact_1.2.3.tar.gz
Windows binaries: r-devel: CausalImpact_1.2.3.zip, r-release: CausalImpact_1.2.3.zip, r-oldrel: CausalImpact_1.2.3.zip
OS X El Capitan binaries: r-release: CausalImpact_1.2.3.tgz
OS X Mavericks binaries: r-oldrel: CausalImpact_1.2.3.tgz
Old sources: CausalImpact archive

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