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 <http://arxiv.org/abs/1506.02494>.

Version: 0.1.4.1
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 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: no
CRAN checks: backShift results

Downloads:

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

Reverse dependencies:

Reverse suggests: CompareCausalNetworks

Linking:

Please use the canonical form https://CRAN.R-project.org/package=backShift to link to this page.