Package: BSPBSS
Title: Bayesian Spatial Blind Source Separation
Version: 1.0.5
Authors@R: c( person("Ben", "Wu", 
              email = "wuben@ruc.edu.cn", 
              role = c("aut", "cre")),
              person("Ying", "Guo",
              email = "yguo2@emory.edu",
              role = "aut"),
              person("Jian", "Kang",
              email = "jiankang@umich.edu",
              role = "aut") )
Description: 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>.
Depends: R (>= 3.4.0), movMF
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.2.1
LinkingTo: Rcpp, RcppArmadillo
Imports: rstiefel, Rcpp, ica, glmnet, gplots, BayesGPfit, svd,
        neurobase, oro.nifti, gridExtra, ggplot2, gtools
SystemRequirements: GNU make
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2022-11-25 02:01:11 UTC; ben
Author: Ben Wu [aut, cre],
  Ying Guo [aut],
  Jian Kang [aut]
Maintainer: Ben Wu <wuben@ruc.edu.cn>
Repository: CRAN
Date/Publication: 2022-11-25 07:20:06 UTC
Built: R 4.5.0; x86_64-apple-darwin20; 2025-04-02 22:44:03 UTC; unix
Archs: BSPBSS.so.dSYM
