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 <doi:10.48550/arXiv.1506.02494>.

Depends: R (≥ 3.1.0)
Imports: methods, clue, igraph, matrixcalc, reshape2, ggplot2, MASS
Suggests: knitr, pander, fields, testthat, pcalg, rmarkdown
Published: 2020-05-06
DOI: 10.32614/CRAN.package.backShift
Author: Christina Heinze-Deml
Maintainer: Christina Heinze-Deml <heinzedeml at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
CRAN checks: backShift results


Reference manual: backShift.pdf
Vignettes: backShift demo


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

Reverse dependencies:

Reverse suggests: CompareCausalNetworks


Please use the canonical form to link to this page.