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SEset

Computing Statistically-Equivalent Path Models

Installation

About

Tools to compute and analyze the set of statistically-equivalent (Gaussian, linear) path models which generate the input precision or (partial) correlation matrix. This procedure is useful for understanding how statistical network models such as the Gaussian Graphical Model (GGM) perform as causal discovery tools. The statistical-equivalence set of a given GGM expresses the uncertainty we have about the sign, size and direction of directed relationships based on the weights matrix of the GGM alone. The derivation of the equivalence set and its use for understanding GGMs as causal discovery tools is described by Ryan, O., Bringmann, L.F., & Schuurman, N.K. (2022) doi:10.31234/osf.io/ryg69.

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Version 1.0.1
Published 2022-03-17 823 days ago
Needs compilation? no
License GPL-3
CRAN checks SEset results

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Maintainer

Maintainer

Oisín Ryan

Authors

Oisín Ryan

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Imports

combinat
Matrix
Rdpack
stats

Suggests

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