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>.

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
DOI:	10.32614/CRAN.package.BSPBSS
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

Documentation:

Reference manual:	BSPBSS.pdf
Vignettes:	BSPBSS-vignette

Downloads:

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

Linking:

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