
Generate the marginal likelihood of a set of observations of the following model structure: pi|alpha ~ Dirichlet(alpha) x|pi ~ Categorical(pi) the model structure and prior parameters are stored in a "CatDirichlet" object. Marginal likelihood is the likelihood of x|alpha
# S3 method for CatDirichlet
marginalLikelihood_bySufficientStatistics(obj, ss, LOG = TRUE, ...)
A "CatDirichlet" object.
Sufficient statistics of x. In Categorical-Dirichlet case the sufficient statistic of sample x can be either x itself, of an "ssCat" object generated by the function sufficientStatistics.CatDirichlet().
Return the log density if set to "TRUE".
Additional arguments to be passed to other inherited types.
numeric, the marginal likelihood.
Murphy, Kevin P. Machine learning: a probabilistic perspective. MIT press, 2012.
@seealso CatDirichlet
, marginalLikelihood.CatDirichlet
# NOT RUN {
obj <- CatDirichlet(gamma=list(alpha=runif(26,1,2),uniqueLabels = letters))
x <- sample(letters,size = 20,replace = TRUE)
marginalLikelihood(obj=obj,x=x,LOG = TRUE) #marginal likelihood
ss <- sufficientStatistics(obj = obj,x=x)
marginalLikelihood_bySufficientStatistics(obj=obj,ss = ss,LOG = TRUE)
# }
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