backShift: Learning Causal Cyclic Graphs from Unknown Shift Interventions

Code for 'backShift', an algorithm to estimate the connectivity matrix of a directed (possibly cyclic) graph with hidden variables. The underlying system is required to be linear and we assume that observations under different shift interventions are available. For more details, see <arXiv:1506.02494>.

Version: 0.1.4.3
Depends: R (≥ 3.1.0)
Imports: methods, clue, igraph, matrixcalc, reshape2, ggplot2, MASS
Suggests: knitr, pander, fields, testthat, pcalg, rmarkdown
Published: 2020-05-06
Author: Christina Heinze-Deml
Maintainer: Christina Heinze-Deml <heinzedeml at stat.math.ethz.ch>
BugReports: https://github.com/christinaheinze/backShift/issues
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://github.com/christinaheinze/backShift
NeedsCompilation: yes
CRAN checks: backShift results

Downloads:

Reference manual: backShift.pdf
Vignettes: backShift demo
Package source: backShift_0.1.4.3.tar.gz
Windows binaries: r-devel: backShift_0.1.4.3.zip, r-release: backShift_0.1.4.3.zip, r-oldrel: backShift_0.1.4.3.zip
macOS binaries: r-release (arm64): backShift_0.1.4.3.tgz, r-release (x86_64): backShift_0.1.4.3.tgz, r-oldrel: backShift_0.1.4.3.tgz
Old sources: backShift archive

Reverse dependencies:

Reverse suggests: CompareCausalNetworks

Linking:

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