Package: CausalImpact 1.3.0

Alain Hauser

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.

Authors:Kay H. Brodersen <[email protected]>, Alain Hauser <[email protected]>

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CausalImpact.pdf |CausalImpact.html
CausalImpact/json (API)

# Install 'CausalImpact' in R:
install.packages('CausalImpact', repos = c('https://google.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/google/causalimpact/issues

On CRAN:

2 exports 1.7k stars 10.50 score 34 dependencies 2 dependents 8 mentions 268 scripts 8.4k downloads

Last updated 2 years agofrom:e38049fdf1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 14 2024
R-4.5-winOKSep 14 2024
R-4.5-linuxOKSep 14 2024
R-4.4-winOKSep 14 2024
R-4.4-macOKSep 14 2024
R-4.3-winOKSep 14 2024
R-4.3-macOKSep 14 2024

Exports:as.CausalImpactCausalImpact

Dependencies:assertthatBoomBoomSpikeSlabbstsclicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithrxtszoo

CausalImpact

Rendered fromCausalImpact.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2020-12-20
Started: 2017-04-03