<commit_before>#ifndef STAN_MATH_PRIM_MAT_PROB_ORDERED_LOGISTIC_GLM_LPMF_HPP
#define STAN_MATH_PRIM_MAT_PROB_ORDERED_LOGISTIC_GLM_LPMF_HPP

#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
#include <stan/math/prim/scal/meta/partials_return_type.hpp>
#include <stan/math/prim/scal/meta/operands_and_partials.hpp>
#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
#include <stan/math/prim/scal/err/check_bounded.hpp>
#include <stan/math/prim/scal/err/check_finite.hpp>
#include <stan/math/prim/mat/fun/value_of_rec.hpp>
#include <stan/math/prim/arr/fun/value_of_rec.hpp>
#include <stan/math/prim/mat/meta/as_column_vector_or_scalar.hpp>
#include <stan/math/prim/scal/meta/as_column_vector_or_scalar.hpp>
#include <stan/math/prim/scal/meta/include_summand.hpp>
#include <stan/math/prim/scal/fun/size_zero.hpp>
#include <stan/math/prim/mat/err/check_ordered.hpp>
#include <stan/math/prim/arr/err/check_ordered.hpp>
#include <stan/math/prim/scal/fun/log1p_exp.hpp>
#include <cmath>

namespace stan {
namespace math {

/**
 * 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).
 *
 * @tparam T_y type of integer vector of dependent variables (labels)
 * @tparam T_x_scalar type of elements in the matrix of independent variables
 * (features)
 * @tparam T_beta T_beta type of the weight vector
 * @tparam T_cuts T_beta type of the cutpoints vector
 * @param y integer vector parameter
 * @param x design matrix<commit_msg>fixed headers<commit_after>#ifndef STAN_MATH_PRIM_MAT_PROB_ORDERED_LOGISTIC_GLM_LPMF_HPP
#define STAN_MATH_PRIM_MAT_PROB_ORDERED_LOGISTIC_GLM_LPMF_HPP

#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
#include <stan/math/prim/scal/meta/partials_return_type.hpp>
#include <stan/math/prim/scal/meta/operands_and_partials.hpp>
#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
#include <stan/math/prim/scal/err/check_bounded.hpp>
#include <stan/math/prim/scal/err/check_finite.hpp>
#include <stan/math/prim/mat/fun/value_of_rec.hpp>
#include <stan/math/prim/arr/fun/value_of_rec.hpp>
#include <stan/math/prim/mat/meta/as_column_vector_or_scalar.hpp>
#include <stan/math/prim/scal/meta/as_column_vector_or_scalar.hpp>
#include <stan/math/prim/scal/meta/include_summand.hpp>
#include <stan/math/prim/scal/fun/size_zero.hpp>
#include <stan/math/prim/mat/err/check_ordered.hpp>
#include <stan/math/prim/arr/err/check_ordered.hpp>
#include <stan/math/prim/mat/fun/log1m_exp.hpp>
#include <cmath>

namespace stan {
namespace math {

/**
 * 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).
 *
 * @tparam T_y type of integer vector of dependent variables (labels)
 * @tparam T_x_scalar type of elements in the matrix of independent variables
 * (features)
 * @tparam T_beta T_beta type of the weight vector
 * @tparam T_cuts T_beta type of the cutpoints vector
 * @param y integer vector parameter
 * @param x design matrix
{'fraction_non_alphanumeric': 0.11487576637625041, 'fraction_numerical': 0.0006453694740238787, 'mean_word_length': 5.681034482758621, 'pattern_counts': {'":': 0, '<': 35, '<?xml version=': 0, '>': 35, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2555596', 'n_tokens_mistral': 1140, 'n_tokens_neox': 1125, 'n_words': 220}