Package: BSPBSS 1.0.5

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>.

Authors:Ben Wu [aut, cre], Ying Guo [aut], Jian Kang [aut]

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Peer review:

Bug tracker:https://github.com/benwu233/bspbss/issues

On CRAN:

7 exports 4 stars 1.03 score 60 dependencies 5 scripts 318 downloads

Last updated 2 years agofrom:da762898b9. Checks:OK: 1 NOTE: 8. Indexed: yes.

Exports:init_bspbsslevelplot2Dmcmc_bspbssoutput_niipre_niisim_2Dimagesum_mcmc_bspbss

Dependencies:abindBayesGPfitbitopscaToolscliclueclustercodetoolscolorspacefansifarverforeachggplot2glmnetgluegplotsgridExtragtablegtoolsicaisobanditeratorsKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmovMFmunsellneurobasenlmeoro.niftipillarpkgconfigR.methodsS3R.ooR.utilsR6RColorBrewerRcppRcppArmadilloRcppEigenrlangRNiftirstiefelscalesshapeskmeansslamsurvivalsvdtibbleutf8vctrsviridisLitewithr