pymc.DirichletMultinomial

class pymc.DirichletMultinomial(name, *args, **kwargs)

Dirichlet Multinomial log-likelihood.

Dirichlet mixture of Multinomials distribution, with a marginalized PMF.

\[f(x \mid n, a) = \frac{\Gamma(n + 1)\Gamma(\sum a_k)} {\Gamma(n + \sum a_k)} \prod_{k=1}^K \frac{\Gamma(x_k + a_k)} {\Gamma(x_k + 1)\Gamma(a_k)}\]

Support	\(x \in \{0, 1, \ldots, n\}\) such that \(\sum x_i = n\)
Mean	\(n \frac{a_i}{\sum{a_k}}\)

Parameters

ntensor_like of int

Total counts in each replicate (n > 0).

atensor_like of float

Dirichlet concentration parameters (a > 0). The number of categories is given by the length of the last axis.

Methods

DirichletMultinomial.__init__(*args, **kwargs)
DirichletMultinomial.dist(n, a, *args, **kwargs)	Creates a tensor variable corresponding to the cls distribution.
DirichletMultinomial.logp(n, a)	Calculate log-probability of DirichletMultinomial distribution at specified value.
DirichletMultinomial.moment(size, n, a)

Attributes

rv_op