marginalLikelihood.CatDP {bbricks}R Documentation

Marginal likelihood of a "CatDP" object


Generate the marginal likelihood of the following model structure:

pi|alpha \sim DP(alpha,U)

x|pi \sim Categorical(pi)

where DP(alpha,U) is a Dirichlet Process on positive integers, alpha is the "concentration parameter" of the Dirichlet Process, U is the "base measure" of this Dirichlet process, it is an uniform distribution on all positive integers.Categorical() is the Categorical distribution. See dCategorical for the definition of the Categorical distribution.
In the case of CatDP, x can only be positive integers.
The model structure and prior parameters are stored in a "CatDP" object.
Marginal likelihood = p(x|alpha).


## S3 method for class 'CatDP'
marginalLikelihood(obj, x, LOG = TRUE, ...)



A "CatDP" object.


integer, the elements of the vector must all greater than 0, the samples of a Categorical distribution.


Return the log density if set to "TRUE".


Additional arguments to be passed to other inherited types.


numeric, the marginal likelihood.

See Also

CatDP, marginalLikelihood_bySufficientStatistics.CatDP

[Package bbricks version 0.1.4 Index]