Learning Causal Cyclic Graphs from Unknown Shift Interventions
jointDiag, clue, pcalg, igraph, matrixcalc, reshape2
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>.

jointDiag, clue, pcalg, igraph, matrixcalc, reshape2, ggplot2

methods, jointDiag, clue, igraph, matrixcalc, reshape2,
ggplot2, mvnmle, MASS
knitr, pander, fields, testthat, pcalg, rmarkdown

methods, clue, igraph, matrixcalc, reshape2, ggplot2, mvnmle,
MASS
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 <arXiv:1506.02494>.

methods, clue, igraph, matrixcalc, reshape2, ggplot2, MASS

Authors@R: person("Phill", "Clarke", email = "phill@starkingdom.co.uk",
role = c("aut", "cre"))
Provides convenience functions for the Backblaze B2 cloud storage
API (see https://www.backblaze.com/b2/docs/). All B2 API calls are mapped
to equivalent R functions. Files can be easily uploaded, downloaded and
deleted from B2, all from within R programs.

Extracts the Backbone from Weighted Graphs
c(
person("Rachel", "Domagalski", email = "domagal9@msu.edu", role = c("aut", "cre")),
person("Zachary", "Neal", email = "zpneal@msu.edu", role = "aut"),
person("Bruce", "Sagan", email = "bsagan@msu.edu", role = "aut"))
Provides methods for extracting from a weighted graph
a binary or signed backbone that retains only the significant edges.
The user may input a weighted graph, or a bipartite graph
from which a weighted graph is first constructed via projection.
Backbone extraction methods include the stochastic degree sequence model (Neal, Z. P. (2014). <doi:10.1016/j.socnet.2014.06.001>),
hypergeometric model (Neal, Z. (2013). <doi:10.1007/s13278-013-0107-y>),
the fixed degree sequence model (Zweig, K. A., and Kaufmann, M. (2011). <doi:10.1007/s13278-011-0021-0>),
as well as a universal threshold method.
Rachel Domagalski [aut, cre],
Zachary Neal [aut],
Bruce Sagan [aut]