Package: CausalMBSTS 0.1.1

CausalMBSTS: MBSTS Models for Causal Inference and Forecasting

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.

Authors:Iavor Bojinov [aut], Fiammetta Menchetti [aut, cre], Victoria L. Prince [ctb], Ista Zahn [ctb]

CausalMBSTS_0.1.1.tar.gz
CausalMBSTS_0.1.1.zip(r-4.7)CausalMBSTS_0.1.1.zip(r-4.6)CausalMBSTS_0.1.1.zip(r-4.5)
CausalMBSTS_0.1.1.tgz(r-4.6-any)CausalMBSTS_0.1.1.tgz(r-4.5-any)
CausalMBSTS_0.1.1.tar.gz(r-4.7-any)CausalMBSTS_0.1.1.tar.gz(r-4.6-any)
CausalMBSTS_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
CausalMBSTS/json (API)
NEWS

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

Bug tracker:https://github.com/fmenchetti/causalmbsts/issues

On CRAN:

Conda:

4.90 score 16 stars 6 scripts 235 downloads 4 exports 36 dependencies

Last updated from:04fd3bcb29. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE163
source / vignettesOK196
linux-release-x86_64NOTE160
macos-release-arm64NOTE149
macos-oldrel-arm64NOTE178
windows-develNOTE128
windows-releaseNOTE126
windows-oldrelNOTE115
wasm-releaseOK107

Exports:as.mbstsCausalMBSTSmcmcmodel

Dependencies:CholWishartclicolorspacecpp11farverforecastfracdiffgenericsggplot2gluegtableisobandKFASlabelinglatticelifecyclelmtestmagrittrMASSMatrixMixMatrixnlmennetR6RColorBrewerRcppRcppArmadillorlangS7scalestimeDateurcavctrsviridisLitewithrzoo

Working example of causal inference with CausalMBSTS package

Rendered fromCausalMBSTS.Rmdusingknitr::rmarkdownon May 26 2026.

Last update: 2020-10-23
Started: 2020-09-30