Infers the causal effect of an intervention on a multivariate response through the use of Multivariate Bayesian Structural Time Series models (MBSTS) as described in Menchetti & Bojinov (2020) <arXiv:2006.12269>. The package also includes functions for model building and forecasting.
| Version: | 0.1.0 |
| Depends: | KFAS, R (≥ 3.5.0) |
| Imports: | CholWishart, forecast, MASS, Matrix, MixMatrix |
| Suggests: | testthat, knitr, rmarkdown |
| Published: | 2020-11-03 |
| Author: | Iavor Bojinov [aut], Fiammetta Menchetti [aut, cre], Victoria L. Prince [ctb], Ista Zahn [ctb] |
| Maintainer: | Fiammetta Menchetti <fiammetta.menchetti at gmail.com> |
| BugReports: | https://github.com/FMenchetti/CausalMBSTS/issues |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| CRAN checks: | CausalMBSTS results |
| Reference manual: | CausalMBSTS.pdf |
| Vignettes: |
Working example of causal inference with CausalMBSTS package |
| Package source: | CausalMBSTS_0.1.0.tar.gz |
| Windows binaries: | r-devel: CausalMBSTS_0.1.0.zip, r-release: CausalMBSTS_0.1.0.zip, r-oldrel: CausalMBSTS_0.1.0.zip |
| macOS binaries: | r-release: CausalMBSTS_0.1.0.tgz, r-oldrel: CausalMBSTS_0.1.0.tgz |
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