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
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CausalMBSTS.pdf |CausalMBSTS.html✨
CausalMBSTS/json (API)
NEWS

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

Peer review:

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

On CRAN:

4 exports 16 stars 1.87 score 48 dependencies 6 scripts 280 downloads

Last updated 3 years agofrom:04fd3bcb29. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 28 2024
R-4.5-winNOTEAug 28 2024
R-4.5-linuxNOTEAug 28 2024
R-4.4-winNOTEAug 28 2024
R-4.4-macNOTEAug 28 2024
R-4.3-winOKAug 28 2024
R-4.3-macOKAug 28 2024

Exports:as.mbstsCausalMBSTSmcmcmodel

Dependencies:CholWishartclicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonliteKFASlabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvMixMatrixmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo

Working example of causal inference with CausalMBSTS package

Rendered fromCausalMBSTS.Rmdusingknitr::rmarkdownon Aug 28 2024.

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