dbnR (version 0.7.1)

plot_dynamic_network: Plots a dynamic Bayesian network in a hierarchical way

Description

To plot the DBN, this method first computes a hierarchical structure for a time slice and replicates it for each slice. Then, it calculates the relative position of each node with respect to his equivalent in the first slice. The result is a net where each time slice is ordered and separated from one another, where the leftmost slice is the oldest and the rightmost represents the present time.

Usage

plot_dynamic_network(structure, offset = 200)

Arguments

structure

the structure or fit of the network.

offset

the blank space between time slices

Value

the visualization of the DBN

Examples

# NOT RUN {
size = 3
dt_train <- dbnR::motor[200:2500]
net <- learn_dbn_struc(dt_train, size)
plot_dynamic_network(net)
# }