MAP estimate of a "CatDirichlet" object

Description

Generate the MAP estimate of "pi" in following Categorical-Dirichlet 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.
MAP is pi_MAP = argmax p(pi|alpha,x).

Usage

## S3 method for class 'CatDirichlet'
MAP(obj, ...)

Arguments

Value

A numeric vector, the MAP estimate of "pi".

References

Murphy, Kevin P. Machine learning: a probabilistic perspective. MIT press, 2012.

See Also

CatDirichlet

Examples

obj <- CatDirichlet(gamma=list(alpha=rep(1,26),uniqueLabels = letters))
x <- sample(letters,size = 20,replace = TRUE)
w <- runif(20)
posterior(obj=obj,ss=x,w=w)
MAP(obj)