Stan Math Library
5.0.0
Automatic Differentiation
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return_type_t< T_y, T_loc, T_prec > stan::math::beta_proportion_lpdf | ( | const T_y & | y, |
const T_loc & | mu, | ||
const T_prec & | kappa | ||
) |
The log of the beta density for specified y, location, and precision: beta_proportion_lpdf(y | mu, kappa) = beta_lpdf(y | mu * kappa, (1 - mu) * kappa).
Any arguments other than scalars must be containers of the same size. With non-scalar arguments, the return is the sum of the log pdfs with scalars broadcast as necessary.
The result log probability is defined to be the sum of the log probabilities for each observation/mu/kappa triple.
Prior location, mu, must be contained in (0, 1). Prior precision must be positive.
T_y | type of scalar outcome |
T_loc | type of prior location |
T_prec | type of prior precision |
y | (Sequence of) scalar(s) between zero and one |
mu | (Sequence of) location parameter(s) |
kappa | (Sequence of) precision parameter(s) |
Definition at line 51 of file beta_proportion_lpdf.hpp.