random_dag: Simulate random DAG
In nicolagnecco/causalXtreme: Causal discovery in heavy-tailed models
View source: R/simulation_helpers.R
random_dag R Documentation
Simulate random DAG
Description
Simulates a directed acyclic graph (DAG) and returns its adjacency matrix.
Copyright (c) 2013 Jonas Peters peters@math.ku.dk.
All rights reserved.
Usage
random_dag(p, prob_connect, caus_order = sample(p, p, replace = FALSE))
Arguments
p
Integer — greater than 0. Number of nodes.
prob_connect
Numeric — between 0 and 1. The probability that an edge
i {\rightarrow} j is added to the DAG.
caus_order
Numeric vector. The causal order of the DAG.
If the argument is not provided it is generated randomly.
Value
Square binary matrix. A matrix representing the random DAG.
nicolagnecco/causalXtreme documentation built on April 21, 2024, 4:22 a.m.
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View source: R/simulation_helpers.R
| random_dag | R Documentation |
Simulate random DAG
Description
Simulates a directed acyclic graph (DAG) and returns its adjacency matrix. Copyright (c) 2013 Jonas Peters peters@math.ku.dk. All rights reserved.
Usage
random_dag(p, prob_connect, caus_order = sample(p, p, replace = FALSE))
Arguments
p |
Integer — greater than 0. Number of nodes. |
prob_connect |
Numeric — between 0 and 1. The probability that an edge
|
caus_order |
Numeric vector. The causal order of the DAG. If the argument is not provided it is generated randomly. |
Value
Square binary matrix. A matrix representing the random DAG.
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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