ordered_logistic_glm_lpmf() [2/3]

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  )

inline

Returns the log PMF of the ordinal regression Generalized Linear Model (GLM).

This is equivalent to and faster than ordered_logistic_lpmf(y, x * beta, cuts).

Template Parameters

T_y	type of integer vector of classes. It can be either std::vector<int> or int.
T_x	type of the matrix of independent variables (features)
T_beta	type of the vector of weights
T_cuts	type of the vector of cutpoints

Parameters

y	a scalar or vector of classes. If it is a scalar it will be broadcast - used for all instances. Values should be between 1 and number of classes, including endpoints.
x	design matrix or row vector. If it is a row vector it will be broadcast - used for all instances.
beta	weight vector
cuts	cutpoints vector

Returns

log probability

Exceptions

std::domain_error	If any class is not between 1 and the number of cutpoints plus 2 or if the cutpoint vector is not sorted in ascending order or any input is not finite
std::invalid_argument	if container sizes mismatch.

Definition at line 49 of file ordered_logistic_glm_lpmf.hpp.