Automatic Differentiation
 
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◆ dirichlet_log() [1/2]

template<bool propto, typename T_prob , typename T_prior_size >
return_type_t< T_prob, T_prior_size > stan::math::dirichlet_log ( const T_prob &  theta,
const T_prior_size &  alpha 
)

The log of the Dirichlet density for the given theta and a vector of prior sample sizes, alpha.

Each element of alpha must be greater than 0. Each element of theta must be greater than or 0. Theta sums to 1.

Deprecated:
use dirichlet_lpdf
Parameters
thetaA scalar vector.
alphaPrior sample sizes.
Returns
The log of the Dirichlet density.
Exceptions
std::domain_errorif any element of alpha is less than or equal to 0.
std::domain_errorif any element of theta is less than 0.
std::domain_errorif the sum of theta is not 1.
Template Parameters
T_probType of scalar.
T_prior_sizeType of prior sample sizes.

Definition at line 31 of file dirichlet_log.hpp.