wgtMatrix: Weight Matrix of a Graph, e.g., a simulated DAG

In pcalg: Methods for Graphical Models and Causal Inference

Weight Matrix of a Graph, e.g., a simulated DAG

Description

Given a graph object g, as generated e.g., by randomDAG, return the matrix of its edge weights, the “weight matrix”.

Usage

wgtMatrix(g, transpose = TRUE)

Arguments

g	graph object (package graph) of, say, p nodes, e.g. containing a DAG.
transpose	logical indicating if the weight matrix should be transposed (t(.), see details).

Details

When generating a DAG (e.g. using randomDAG), a graph object is usually generated and edge weights are usually specified. This function extracts the edge weights and arranges them in a matrix M.

If transpose is TRUE (default), M[i,j] is the weight of the edge from j to i. If transpose is false, M[i,j] is the weight of the edge from i to j.

Nowadays, this is a trivial wrapper around as(g, "matrix") using the (coerce) method provided by the graph package.

Value

The p \times p weight matrix M.

Note

This function can not be used to estimate the edge weights in an estimated DAG / CPDAG.

Author(s)

Markus Kalisch

See Also

randomDAG for generating a random DAG; rmvDAG for simulating data from a generated DAG.

Examples

set.seed(123)
g <- randomDAG(n = 5, prob = 0.3) ## generate random DAG
if(require(Rgraphviz)) {
  plot(g)
}

## edge weights as matrix
wgtMatrix(g)

## for comparison: edge weights in graph object
g@edgeData@data

pcalg documentation built on Sept. 26, 2023, 9:06 a.m.