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>.
| 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 |
| DOI: | 10.32614/CRAN.package.backShift |
| 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 |
Documentation:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=backShiftto link to this page.