Bayesian Spatio-Temporal Factor Analysis Model
Bisquare bases for 1-dimensional space
Bisquare bases for 2-dimensional space
Reduced BSTFA function
Full BSTFA function
Print computation summary
Compute log-likelihood
Check effective sample size and geweke diagnostic
Define the initial region of interest.
Create a matrix of bisquare bases for a set of locations.
Create a matrix of bisquare bases for new locations.
Plot a map of interpolated spatially-dependent parameter values.
Plot annual/seasonal behavior at a specific location.
Plot the temporally-dependent factors.
Visualize fourier bases.
Plot a location's time series of estimated/predicted values.
Plot the spatially-dependent parameter for in-sample locations.
Plot trace plots
Estimate/predict values of the time series at a specific location.
Implements Bayesian spatio-temporal factor analysis models for multivariate data observed across space and time. The package provides tools for model fitting via Markov chain Monte Carlo (MCMC), spatial and temporal interpolation, and visualization of latent factors and loadings to support inference and exploration of underlying spatio-temporal patterns. Designed for use in environmental, ecological, or public health applications, with support for posterior prediction and uncertainty quantification. Includes functions such as BSTFA() for model fitting and plot_factor() to visualize the latent processes. Functions are based on and extended from methods described in Berrett, et al. (2020) <doi:10.1002/env.2609>.