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CausalMBSTS (version 0.1.1)

MBSTS Models for Causal Inference and Forecasting

Description

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) . The package also includes functions for model building and forecasting.

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Install

install.packages('CausalMBSTS')

Monthly Downloads

230

Version

0.1.1

License

GPL (>= 3)

Maintainer

Fiammetta Menchetti

Last Published

October 5th, 2021

Functions in CausalMBSTS (0.1.1)

model

Multivariate structural time series model definition
as.mbsts

Definition and estimation of a Multivariate Bayesian Structural Time Series model (MBSTS)
predict.mbsts

Predictions for a given multivariate Bayesian structural time series model
plot.CausalMBSTS

Plotting function for object of class CausalMBSTS
CausalMBSTS

Causal effect estimation in a multivariate setting
print.summary.CausalMBSTS

Format and print the estimated causal effect(s), credible interval(s), and Bayesian p-value(s) into a clear output.
summary.CausalMBSTS

Summary of causal effect estimation results obtained with CausalMBSTS
mcmc

MCMC samples for a given MBSTS model