Generate the MPE 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
dCategorical for the definitions of these distribution.
The model structure and prior parameters are stored in a "CatDirichlet" object.
MPE is pi_MPE = E(pi|alpha,x), E() is the expectation function.
A "CatDirichlet" object.
Additional arguments to be passed to other inherited types.
A numeric vector, the MPE of "pi".
Murphy, Kevin P. Machine learning: a probabilistic perspective. MIT press, 2012.
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