| rPosteriorPredictive.CatDirichlet | R Documentation |
Generate random samples from the posterior predictive distribution of the following structure:
pi|alpha \sim Dir(alpha)
x|pi \sim Categorical(pi)
Where Dir() is the Dirichlet distribution, Categorical() is the Categorical distribution. See ?dDir and dCategorical for the definitions of these distribution.
The model structure and prior parameters are stored in a "CatDirichlet" object
posterior predictive is a distribution of x|alpha
## S3 method for class 'CatDirichlet' rPosteriorPredictive(obj, n, ...)
obj |
A "CatDirichlet" object. |
n |
integer, number of samples. |
... |
Additional arguments to be passed to other inherited types. |
A vector of the same type as obj$gamma$uniqueLabels.
Murphy, Kevin P. Machine learning: a probabilistic perspective. MIT press, 2012.
CatDirichlet, dPosteriorPredictive.CatDirichlet
obj <- CatDirichlet(gamma=list(alpha=runif(26,1,2),uniqueLabels = letters)) rPosteriorPredictive(obj=obj,n=200)