BSPBSS
1.0.6Bayesian Spatial Blind Source Separation
Overview
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.
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Package metadata
- First published
- 2022-09-02
- Total releases
- 5 / 4 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.4.0
- Download size
- 356 KB
- Installed size
- not tracked yet
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- not tracked yet