alpha.star: Estimate the optimal imaginary sample size for BDe(u)
Description
Estimate the optimal value of the imaginary sample size for the BDe score,
assuming a uniform prior and given a network structure and a data set.
Usage
alpha.star(x, data, debug = FALSE)
Value
alpha.star() returns a positive number, the estimated optimal imaginary
sample size value.
Arguments
x
an object of class bn (for bn.fit and custom.fit)
or an object of class bn.fit (for bn.net).
data
a data frame containing the variables in the model.
debug
a boolean value. If TRUE a lot of debugging output is
printed; otherwise the function is completely silent.
Author
Marco Scutari
References
Steck H (2008). "Learning the Bayesian Network Structure: Dirichlet Prior
versus Data". Proceedings of the 24th Conference on Uncertainty in
Artificial Intelligence, 511--518.
data(learning.test)
dag = hc(learning.test, score = "bic")
for (i in1:3) {
a = alpha.star(dag, learning.test)
dag = hc(learning.test, score = "bde", iss = a)
}#FOR