causalsim: causalsim: A package to explore linear causal DAGs
In gmonette/causalsim: Covariance Matrix of a Causal Graph
causalsim R Documentation
causalsim: A package to explore linear causal DAGs
Description
The causalsim package uses a matrix containing the
coefficients and standard deviations of the unique
independent components of a linear causal
DAG to generate the marginal covariance matrix and to
calculate the value of coefficients of
linear models applied to a population generated by
the causal DAG.
Details
See coefx for an extended example.
gmonette/causalsim documentation built on April 21, 2022, 1:40 a.m.
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| causalsim | R Documentation |
causalsim: A package to explore linear causal DAGs
Description
The causalsim package uses a matrix containing the coefficients and standard deviations of the unique independent components of a linear causal DAG to generate the marginal covariance matrix and to calculate the value of coefficients of linear models applied to a population generated by the causal DAG.
Details
See coefx for an extended example.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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