README.md

In christinaheinze/backShift: Learning Causal Cyclic Graphs from Unknown Shift Interventions

backShift

R 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.

Installation

From CRAN

install.packages("backShift")

Dependencies

If getOptions("repos") does not contain Bioconductor ("BioCsoft"), the packages graph and RBGL need to be downloaded from Bioconductor with

source("http://bioconductor.org/biocLite.R") 
biocLite(c("graph","RBGL"))

From Github with devtools

devtools::install_github("christinaheinze/backShift")

Code

See the package vignettes for more details.

References

D. Rothenhaeusler, C. Heinze, J. Peters and N. Meinshausen. "backShift: Learning causal cyclic graphs from unknown shift interventions". Advances in Neural Information Processing Systems (NIPS) 28, 2015. arXiv.

christinaheinze/backShift documentation built on May 13, 2019, 7 p.m.