bnlearn (version 0.8)

rbn: Generate random data from a given Bayesian network

Description

Generate random data from a given Bayesian network.

Usage

rbn(x, n, data, debug = FALSE)

Arguments

x

an object of class bn.

n

non-negative integer giving the number of observations to generate.

data

a data frame, containing the data the Bayesian network was learned from.

debug

a boolean value. If TRUE a lot of debugging output is printed; otherwise the function is completely silent.

Value

• A data frame with the same structure (column names and data types) of the data parameter.

References

K. Korb and A. Nicholson. Bayesian artificial intelligence. Chapman and Hall, 2004.

Examples

library(bnlearn)
data(learning.test)
res = gs(learning.test)
res = set.arc(res, "A", "B")
par(mfrow = c(1,2))
plot(res)
sim = rbn(res, 500, learning.test)
plot(gs(sim))