plot_graph: Plot graphical model
In jialiwang1211/GCMlasso: Bayesian Gaussian graphical model with clustering structure for ordered variables.
Description
Usage
Arguments
Examples
Description
Plot the conditional dependence between variables on the latent scale.
The assocations between variables are computed from the precision matrices
from the MCMC, and the percentage of edges to be included in the graph
is determined by the edge_perc value.
Usage
1
plot_graph(GCMlasso_obj = CMlasso_obj, var, edge_perc, seed = 1)
Arguments
GCMlasso_obj
GCMlasso object.
var
variables in the graph.
edge_perc
cut-off quantile value of edge inclusion.
seed
a random integer.
Examples
1
plot_graph(GCMlasso_obj,var=1:15,edge_perc=0.65)
jialiwang1211/GCMlasso documentation built on May 14, 2019, 12:55 a.m.
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Description Usage Arguments Examples
Description
Plot the conditional dependence between variables on the latent scale.
The assocations between variables are computed from the precision matrices
from the MCMC, and the percentage of edges to be included in the graph
is determined by the edge_perc value.
Usage
1 | plot_graph(GCMlasso_obj = CMlasso_obj, var, edge_perc, seed = 1)
|
Arguments
GCMlasso_obj |
|
var |
variables in the graph. |
edge_perc |
cut-off quantile value of edge inclusion. |
seed |
a random integer. |
Examples
1 | plot_graph(GCMlasso_obj,var=1:15,edge_perc=0.65)
|
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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