BSPBSS
Bayesian Spatial Blind Source Separation
Gibbs sampling for Bayesian spatial blind source separation (BSP-BSS). BSP-BSS is designed for spatially dependent signals in high dimensional and large-scale data, such as neuroimaging. The method assumes the expectation of the observed images as a linear mixture of multiple sparse and piece-wise smooth latent source signals, and constructs a Bayesian nonparametric prior by thresholding Gaussian processes. Details can be found in our paper: Wu, B., Guo, Y., & Kang, J. (2024). Bayesian spatial blind source separation via the thresholded gaussian process. Journal of the American Statistical Association, 119(545), 422-433.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.6 |
2026-04-09 windows/windows R-4.5 | BSPBSS_1.0.6.zip |
806.7 KiB |