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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>.
| Version: | 1.0.5 |
| Depends: | R (≥ 3.4.0), movMF |
| Imports: | rstiefel, Rcpp, ica, glmnet, gplots, BayesGPfit, svd, neurobase, oro.nifti, gridExtra, ggplot2, gtools |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, rmarkdown |
| Published: | 2022-11-25 |
| Author: | Ben Wu [aut, cre], Ying Guo [aut], Jian Kang [aut] |
| Maintainer: | Ben Wu <wuben at ruc.edu.cn> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| SystemRequirements: | GNU make |
| Materials: | README |
| CRAN checks: | BSPBSS results |
| Reference manual: | BSPBSS.pdf |
| Vignettes: |
BSPBSS-vignette |
| Package source: | BSPBSS_1.0.5.tar.gz |
| Windows binaries: | r-devel: BSPBSS_1.0.5.zip, r-release: BSPBSS_1.0.5.zip, r-oldrel: BSPBSS_1.0.5.zip |
| macOS binaries: | r-release (arm64): BSPBSS_1.0.5.tgz, r-oldrel (arm64): BSPBSS_1.0.5.tgz, r-release (x86_64): BSPBSS_1.0.5.tgz, r-oldrel (x86_64): BSPBSS_1.0.5.tgz |
| Old sources: | BSPBSS archive |
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