fully_connected_network: Fully-connected graph.
In ntwk: Statistical Inference for Network Time Series
Description
Usage
Arguments
Value
Examples
Description
Fully-connected graph.
Usage
1
fully_connected_network(d, theta_1, theta_2, directed = FALSE)
Arguments
d
Number of nodes.
theta_1
Off-diagonal value or network effect.
theta_2
Diagonal value or momentum effect.
directed
Boolean if lower triangular is the opposite
to the upper triangular matrix.
Value
A d x d adjacency matrix of a fully-connected graph.
Examples
1
2
3
4
d <- 10
theta_2 <- 2
theta_1 <- 1
fully_connected_network(d = d, theta_1 = theta_1, theta_2 = theta_2)
ntwk documentation built on Sept. 13, 2021, 9:07 a.m.
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Description Usage Arguments Value Examples
Description
Fully-connected graph.
Usage
1 | fully_connected_network(d, theta_1, theta_2, directed = FALSE)
|
Arguments
d |
Number of nodes. |
theta_1 |
Off-diagonal value or network effect. |
theta_2 |
Diagonal value or momentum effect. |
directed |
Boolean if lower triangular is the opposite to the upper triangular matrix. |
Value
A d x d adjacency matrix of a fully-connected graph.
Examples
1 2 3 4 | d <- 10
theta_2 <- 2
theta_1 <- 1
fully_connected_network(d = d, theta_1 = theta_1, theta_2 = theta_2)
|
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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