PCBN (version 0.1.1)

logLik.PCBN: Log-likelihood of a PCBN object

Description

This function computes the log-likelihood of the PCBN model given a dataset of i.i.d. observations uniformly (or approximatively uniformly) distributed on \([0,1]\). This is the same as the logarithm of the density of the PCBN at the observations.

Usage

# S3 method for PCBN
logLik(object, data_uniform, ...)

Value

the log-likelihood of the PCBN model for the given dataset

Arguments

object

the PCBN object

data_uniform

the dataset for which the log-likelihood is computed. It must have already been standardized to uniform margins.

...

other arguments, ignored for the moment

Examples

DAG = create_empty_DAG(3)
DAG = bnlearn::set.arc(DAG, 'U1', 'U3')
DAG = bnlearn::set.arc(DAG, 'U2', 'U3')

order_hash = r2r::hashmap()
order_hash[['U3']] = c("U1", "U2")

fam = matrix(c(0, 0, 1,
               0, 0, 1,
               0, 0, 0), byrow = TRUE, ncol = 3)
tau = 0.2 * fam

my_PCBN = new_PCBN(
  DAG, order_hash,
  copula_mat = list(tau = tau, fam = fam))

mydata = PCBN_sim(my_PCBN, N = 10)

logLik(my_PCBN, mydata)