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 <>.

Depends: R (≥ 3.1.0)
Imports: methods, jointDiag, clue, igraph, matrixcalc, reshape2, ggplot2, mvnmle, MASS
Suggests: knitr, pander, fields, testthat, pcalg, rmarkdown
Published: 2017-01-09
Author: Christina Heinze-Deml
Maintainer: Christina Heinze-Deml <heinzedeml at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: backShift results


Reference manual: backShift.pdf
Vignettes: backShift demo
Package source: backShift_0.1.4.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: backShift_0.1.4.1.tgz
OS X Mavericks binaries: r-oldrel: backShift_0.1.4.1.tgz
Old sources: backShift archive

Reverse dependencies:

Reverse suggests: CompareCausalNetworks


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