Spatiotemporal Propagation for Multivariate Bayesian Dynamic Learning

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+) . This methodology enables efficient Bayesian multivariate spatiotemporal modeling, utilizing dynamic predictive stacking to improve inference across multivariate time series of spatial datasets. The core functions leverage 'C++' for high-performance computation, making the framework well-suited for large-scale spatiotemporal data analysis in parallel computing environments.

spFFBS

Overview

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.

Installation

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")

Usage

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!

Contacts