Package: BSPBSS
Title: Bayesian Spatial Blind Source Separation
Version: 1.0.6
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, B., Guo, Y., & Kang, J. (2024). Bayesian spatial blind source separation via the thresholded gaussian process. Journal of the American Statistical Association, 119(545), 422-433.
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: 2025-10-16 09:04:09 UTC; ben
Author: Ben Wu [aut, cre],
  Ying Guo [aut],
  Jian Kang [aut]
Maintainer: Ben Wu <wuben@ruc.edu.cn>
Repository: CRAN
Date/Publication: 2025-10-16 11:50:06 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-28 00:07:16 UTC; unix
Archs: BSPBSS.so.dSYM
