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>.


Reference manual

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install.packages("backShift") by Christina Heinze-Deml, 5 months ago


Report a bug at https://github.com/christinaheinze/backShift/issues

Browse source code at https://github.com/cran/backShift

Authors: Christina Heinze-Deml <heinzedeml@stat.math.ethz.ch>

Documentation:   PDF Manual  

GPL license

Imports methods, jointDiag, clue, igraph, matrixcalc, reshape2, ggplot2, mvnmle, MASS

Suggests knitr, pander, fields, testthat, pcalg, rmarkdown

Suggested by CompareCausalNetworks.

See at CRAN