generate_random_network_exp: Generate a random DBN and a sampled dataset

In dbnR: Dynamic Bayesian Network Learning and Inference

Generate a random DBN and a sampled dataset

Description

This function generates both a random DBN and a dataset that can be used to learn its structure from data. It's intended for experimental use.

Usage

generate_random_network_exp(
  n_vars,
  size,
  min_mu,
  max_mu,
  min_sd,
  max_sd,
  min_coef,
  max_coef,
  seed = NULL
)

Arguments

n_vars	number of desired variables per time-slice
size	desired size of the networks
min_mu	minimum mean allowed for the variables
max_mu	maximum mean allowed for the variables
min_sd	minimum standard deviation allowed for the variables
max_sd	maximum standard deviation allowed for the variables
min_coef	minimum coefficient allowed for the parent nodes
max_coef	maximum coefficient allowed for the parent nodes
seed	the seed of the experiment

Value

a list with the original network structure and the sampled dataset

dbnR documentation built on June 22, 2024, 10:54 a.m.