CRAN/E | BSPBSS

BSPBSS

Bayesian Spatial Blind Source Separation

Installation

About

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.

System requirements GNU make

Key Metrics

Version 1.0.5
R ≥ 3.4.0
Published 2022-11-25 490 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks BSPBSS results

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Maintainer

Maintainer

Ben Wu

wuben@ruc.edu.cn

Authors

Ben Wu

aut / cre

Ying Guo

aut

Jian Kang

aut

Material

README
Reference manual
Package source

Vignettes

BSPBSS-vignette

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

BSPBSS archive

Depends

R ≥ 3.4.0
movMF

Imports

rstiefel
Rcpp
ica
glmnet
gplots
BayesGPfit
svd
neurobase
oro.nifti
gridExtra
ggplot2
gtools

Suggests

knitr
rmarkdown

LinkingTo

Rcpp
RcppArmadillo