BSSoverSpace: Blind Source Separation for Multivariate Spatial Data using Eigen Analysis

Provides functions for blind source separation over multivariate spatial data, and useful statistics for evaluating performance of estimation on mixing matrix. 'BSSoverSpace' is based on an eigen analysis of a positive definite matrix defined in terms of multiple normalized spatial local covariance matrices, and thus can handle moderately high-dimensional random fields. This package is an implementation of the method described in Zhang, Hao and Yao (2022)<arXiv:2201.02023>.

Version: 0.1.0
Imports: SpatialBSS, expm, rSPDE
Suggests: knitr, rmarkdown
Published: 2022-11-10
Author: Sixing Hao [aut, cre]
Maintainer: Sixing Hao <s.hao3 at>
License: GPL-3
NeedsCompilation: no
CRAN checks: BSSoverSpace results


Reference manual: BSSoverSpace.pdf
Vignettes: Introduction to BSSoverSpace


Package source: BSSoverSpace_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BSSoverSpace_0.1.0.tgz, r-oldrel (arm64): BSSoverSpace_0.1.0.tgz, r-release (x86_64): BSSoverSpace_0.1.0.tgz, r-oldrel (x86_64): BSSoverSpace_0.1.0.tgz


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