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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

VersionRepositoryFileSize
1.0.6 rolling linux/jammy R-4.5 BSPBSS_1.0.6.tar.gz 479.3 KiB
1.0.6 rolling linux/noble R-4.5 BSPBSS_1.0.6.tar.gz 482.2 KiB
1.0.6 rolling source/ R- BSPBSS_1.0.6.tar.gz 356.0 KiB
1.0.6 latest linux/jammy R-4.5 BSPBSS_1.0.6.tar.gz 479.3 KiB
1.0.6 latest linux/noble R-4.5 BSPBSS_1.0.6.tar.gz 482.2 KiB
1.0.6 latest source/ R- BSPBSS_1.0.6.tar.gz 356.0 KiB
1.0.6 2026-04-26 source/ R- BSPBSS_1.0.6.tar.gz 356.0 KiB
1.0.6 2026-04-23 source/ R- BSPBSS_1.0.6.tar.gz 356.0 KiB
1.0.6 2026-04-09 windows/windows R-4.5 BSPBSS_1.0.6.zip 806.7 KiB
1.0.5 2025-04-20 source/ R- BSPBSS_1.0.5.tar.gz 354.3 KiB

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