rnet.gnm: Call 'igraph::sample_gnm' to Generate Random Graph Object...
In simcausal: Simulating Longitudinal Data with Causal Inference Applications
View source: R/network_distributions.R
rnet.gnm R Documentation
Call igraph::sample_gnm to Generate Random Graph Object According to the G(n,m) Erdos-Renyi Model
Description
Call igraph::sample_gnm and convert the output to simcausal network matrix.
The parameter m of igraph::sample_gnm is derived from n and m_pn as as.integer(m_pn*n)
Usage
rnet.gnm(n, m_pn)
Arguments
n
Size of the network graph (number of nodes).
m_pn
The total number of edges as a fraction of the sample size n.
Value
A matrix with n rows, each row lists the indices of friends connected to that particular observation.
See Also
rnet.gnp
simcausal documentation built on Oct. 29, 2022, 1:13 a.m.
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View source: R/network_distributions.R
| rnet.gnm | R Documentation |
Call igraph::sample_gnm to Generate Random Graph Object According to the G(n,m) Erdos-Renyi Model
Description
Call igraph::sample_gnm and convert the output to simcausal network matrix.
The parameter m of igraph::sample_gnm is derived from n and m_pn as as.integer(m_pn*n)
Usage
rnet.gnm(n, m_pn)
Arguments
n |
Size of the network graph (number of nodes). |
m_pn |
The total number of edges as a fraction of the sample size |
Value
A matrix with n rows, each row lists the indices of friends connected to that particular observation.
See Also
rnet.gnp
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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