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This package provides the implementation of the Forward Filtering Backward Sampling (FFBS) algorithm with Dynamic Bayesian Predictive Stacking (DYNBPS) integration for multivariate spatiotemporal models, as introduced in “Adaptive Markovian Spatiotemporal Transfer Learning in Multivariate Bayesian Modeling” (Presicce and Banerjee, 2026+). To guarantee the reproducibility of scientific results, in the Markovian-Spatiotemporal-Propagation repository also includes all the scripts of code used for simulations, data analysis, and results presented in the Manuscript and its Supplemental material.
If installing from CRAN, use the following.
install.packages("spFFBS")For a quick installation of the development version, run the
following command in R. We use the devtools R package to
install. Then, check for its presence on your device, otherwise install
it:
if (!require(devtools)) {
install.packages("devtools", dependencies = TRUE)
}Once you have installed devtools, we can proceed. Let’s
install the spFFBS package!
devtools::install_github("lucapresicce/spFFBS")Once successfully installed, load the library in R.
library(spFFBS)Cool! You are ready to start, now you too could perform fast & feasible Bayesian spatiotemporal modeling!
| Author | Luca Presicce (l.presicce@campus.unimib.it) |
| Maintainer | Luca Presicce (l.presicce@campus.unimib.it) |
| Reference | Luca Presicce and Sudipto Banerjee (2026+) “Adaptive Markovian Spatiotemporal Transfer Learning in Multivariate Bayesian Modeling” |
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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