pymc.DirichletMultinomial#
- class pymc.DirichletMultinomial(name, *args, **kwargs)[source]#
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.
- ntensor_like of
Methods
DirichletMultinomial.dist(n, a, *args, **kwargs)Creates a tensor variable corresponding to the cls distribution.