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DESCRIPTION
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DESCRIPTION
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Package: EqVarDAG
Type: Package
Title: Causal Discovery with Equal Variance Assumption
Version: 2.1
Authors@R: as.person(c(
"Wenyu Chen <wenyuc@uw.edu> [aut, cre]",
"Mathias Drton <md5@uw.edu> [aut]",
"Y.Samuel Wang <swang24@uchicago.edu> [aut]"
))
Maintainer: Wenyu Chen <wenyuc@uw.edu>
Description: Prior work has shown that causal structure can be
uniquely identified from observational data when these follow a
structural equation model whose error terms have equal variances.
We show that this fact is implied by an ordering among (conditional) variances.
We demonstrate that ordering estimates of these variances yields
a simple yet state-of-the-art method for causal structure learning
that is readily extendable to high-dimensional problems.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports:
cvTools,
glmnet,
leaps,
RcppEigen,
gtools,
Rglpk,
lpSolve,
scalreg,
RBGL,
igraph,
mvtnorm,
ggm,
RPtests