as_graphNEL

Function to transform an adjacency matrix into a graphNEL object.

A collection of functions for structure learning of causal networks and estimation of joint causal effects from observational Gaussian data. Main algorithm consists of a Markov chain Monte Carlo scheme for posterior inference of causal structures, parameters and causal effects between variables.
References:
F. Castelletti and A. Mascaro (2021) <doi:10.1007/s10260-021-00579-1>,
F. Castelletti and A. Mascaro (2022) <doi:10.48550/arXiv.2201.12003>.

Alessandro Mascaro

BCDAG

Bayesian Structure and Causal Learning of Gaussian Directed
Graphs

Federico Castelletti

as_graphNEL function

<dl><dt>DAG</dt>
<dd>Adjacency matrix of a DAG</dd></dl>

Arguments

Transform adjacency matrix into graphNEL object — as_graphNEL

<dl>

<dt>DAG</dt>
<dd>Adjacency matrix of a DAG</dd>

</dl>

as_graphNEL: Transform adjacency matrix into graphNEL object

Description

Usage

Value

Arguments

Examples