generate8nbn: returns a randomly built /nbn/ object.

In rbmn: Handling Linear Gaussian Bayesian Networks

returns a randomly built /nbn/ object.

Description

To obtain systematic results, you have to call set.seed before hands.

Usage

generate8nbn(rnn=c(3, 7), ppar=0.5, rreg=c(-1, 1), rmu=c(0, 0), rsig=c(0, 1),
	  nona=r.form3names(max(rnn)))

Arguments

rnn	Range of the number of nodes.
ppar	Probabilities (not a range) of the parent occurrence for each ancestor of every node. Can be a vector, cycled as necessary.
rreg	Range of regression coefficients.
rmu	Range of the conditional expectations.
rsig	Range of the conditional standard deviations.
nona	Proposed names for the maximum number of nodes, only the necessary first ones will be used.

Details

Node numbers are uniformly drawn. Parent numbers are independently drawn from all ancestors with the probability associated to the considered node. Regression coefficient are uniformly drawn. Conditional expectations and standard deviations are uniformly drawn.
All range arguments can be given one value instead of two, to precise the unique value to use.

Value

a /nbn/ object, with nodes in topological order.

Examples

 set.seed(1234)
 print8nbn(generate8nbn());
 print8nbn(generate8nbn());

rbmn documentation built on July 9, 2023, 6:37 p.m.