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 et al. (2022+) "Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process" doi:10.1080/01621459.2022.2123336.
- Version1.0.5
- R version≥ 3.4.0
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Last release11/25/2022
Documentation
Team
Ben Wu
Jian Kang
Show author detailsRolesAuthorYing Guo
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 240 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 3,443 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jul 21, 2024 with 142 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Depends1 package
- Imports12 packages
- Suggests2 packages
- Linking To2 packages