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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 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:

Please use the canonical form https://CRAN.R-project.org/package=BSPBSS to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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