1#ifndef STAN_MATH_PRIM_PROB_LOGISTIC_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_LOGISTIC_LPDF_HPP
25template <
bool propto,
typename T_y,
typename T_loc,
typename T_scale,
27 T_y, T_loc, T_scale>* =
nullptr>
30 const T_scale& sigma) {
35 static constexpr const char* function =
"logistic_lpdf";
37 mu,
"Scale parameter", sigma);
41 T_sigma_ref sigma_ref = sigma;
61 = to_ref_if<is_any_autodiff_v<T_y, T_loc, T_scale>>(
inv(sigma_val));
62 const auto& y_minus_mu = to_ref_if<is_autodiff_v<T_scale>>(y_val - mu_val);
63 const auto& y_minus_mu_div_sigma =
to_ref(y_minus_mu * inv_sigma);
66 T_partials_return logp = -
sum(y_minus_mu_div_sigma)
72 if constexpr (is_any_autodiff_v<T_y, T_scale>) {
73 const auto& exp_y_minus_mu_div_sigma =
exp(y_minus_mu_div_sigma);
75 =
to_ref_if<(is_autodiff_v<T_scale> && is_autodiff_v<T_y>)>(
76 (2 / (1 + exp_y_minus_mu_div_sigma) - 1) * inv_sigma);
77 if constexpr (is_autodiff_v<T_y>) {
78 partials<0>(ops_partials) = y_deriv;
80 if constexpr (is_autodiff_v<T_scale>) {
81 partials<2>(ops_partials) = (-y_deriv * y_minus_mu - 1) * inv_sigma;
84 if constexpr (is_autodiff_v<T_loc>) {
85 const auto& exp_mu_div_sigma =
to_ref(
exp(mu_val * inv_sigma));
86 edge<1>(ops_partials).partials_
88 - 2 * exp_mu_div_sigma / (exp_mu_div_sigma +
exp(y_val * inv_sigma)))
91 return ops_partials.build(logp);
94template <
typename T_y,
typename T_loc,
typename T_scale>
97 const T_scale& sigma) {
98 return logistic_lpdf<false>(y, mu, sigma);
require_all_not_t< is_nonscalar_prim_or_rev_kernel_expression< std::decay_t< Types > >... > require_all_not_nonscalar_prim_or_rev_kernel_expression_t
Require none of the types satisfy is_nonscalar_prim_or_rev_kernel_expression.
return_type_t< T_y_cl, T_loc_cl, T_scale_cl > logistic_lpdf(const T_y_cl &y, const T_loc_cl &mu, const T_scale_cl &sigma)
The log of a logistic density for y with the specified location and scale parameters.
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
int64_t size(const T &m)
Returns the size (number of the elements) of a matrix_cl or var_value<matrix_cl<T>>.
bool size_zero(const T &x)
Returns 1 if input is of length 0, returns 0 otherwise.
T to_ref_if(T &&a)
No-op that should be optimized away.
fvar< T > log(const fvar< T > &x)
fvar< T > log1p_exp(const fvar< T > &x)
auto as_value_column_array_or_scalar(T &&a)
Extract the value from an object and for eigen vectors and std::vectors convert to an eigen column ar...
void check_consistent_sizes(const char *)
Trivial no input case, this function is a no-op.
void check_finite(const char *function, const char *name, const T_y &y)
Return true if all values in y are finite.
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
fvar< T > inv(const fvar< T > &x)
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
void check_positive_finite(const char *function, const char *name, const T_y &y)
Check if y is positive and finite.
fvar< T > exp(const fvar< T > &x)
typename ref_type_if< is_autodiff_v< T >, T >::type ref_type_if_not_constant_t
typename partials_return_type< Args... >::type partials_return_t
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...