logScoreNormal.bn.list: Normal-inverse-gamma (with g-prior) Log marginal likelihood.

In rjbgoudie/structmcmc: Structural inference for Bayesian Networks and Variable Selection.

Description

Compute the log marginal likelihood of the supplied Bayesian Networks.

Usage

  ## S3 method for class 'bn.list'
 logScoreNormal(x, data,
    cache = new.env(hash = TRUE), ...)

Arguments

x	An object of class "bn.list", the Bayesian Networks for which the marginal likelihood are computed.
data	A matrix, with columns giving the values of each random variable.
cache	Optionally, provide an environment with cached local scores for this data.
...	Further arguments, currently unused.

Details

The data is scored as continuous, using a form of the Normal Prior.

Value

A numeric vector of length 1, giving the log marginal likelihood. The environment 'cache' will also be updated because its scope is global.

See Also

logScoreNormal.bn, logScoreNormal

rjbgoudie/structmcmc documentation built on Nov. 3, 2020, 3:41 a.m.