Stan Math Library
5.0.0
Automatic Differentiation
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#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/as_column_vector_or_scalar.hpp>
#include <stan/math/prim/fun/as_array_or_scalar.hpp>
#include <stan/math/prim/fun/exp.hpp>
#include <stan/math/prim/fun/isfinite.hpp>
#include <stan/math/prim/fun/log1m_exp.hpp>
#include <stan/math/prim/fun/scalar_seq_view.hpp>
#include <stan/math/prim/fun/size.hpp>
#include <stan/math/prim/fun/size_zero.hpp>
#include <stan/math/prim/fun/to_ref.hpp>
#include <stan/math/prim/fun/value_of.hpp>
#include <stan/math/prim/functor/partials_propagator.hpp>
#include <cmath>
Go to the source code of this file.
Namespaces | |
namespace | stan |
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation from C or the boost::math::lgamma implementation. | |
namespace | stan::math |
Matrices and templated mathematical functions. | |
Functions | |
template<bool propto, typename T_y , typename T_x , typename T_beta , typename T_cuts , require_matrix_t< T_x > * = nullptr, require_all_col_vector_t< T_beta, T_cuts > * = nullptr> | |
return_type_t< T_x, T_beta, T_cuts > | stan::math::ordered_logistic_glm_lpmf (const T_y &y, const T_x &x, const T_beta &beta, const T_cuts &cuts) |
Returns the log PMF of the ordinal regression Generalized Linear Model (GLM). | |
template<typename T_y , typename T_x , typename T_beta , typename T_cuts > | |
return_type_t< T_x, T_beta, T_cuts > | stan::math::ordered_logistic_glm_lpmf (const T_y &y, const T_x &x, const T_beta &beta, const T_cuts &cuts) |