1#ifndef STAN_MATH_PRIM_PROB_GUMBEL_CDF_HPP
2#define STAN_MATH_PRIM_PROB_GUMBEL_CDF_HPP
36template <
typename T_y,
typename T_loc,
typename T_scale,
38 T_y, T_loc, T_scale>* =
nullptr>
40 const T_scale&
beta) {
42 using T_partials_array = Eigen::Array<T_partials_return, Eigen::Dynamic, 1>;
46 static constexpr const char* function =
"gumbel_cdf";
48 mu,
"Scale parameter",
beta);
51 T_beta_ref beta_ref =
beta;
67 const auto& scaled_diff
68 = to_ref_if<!is_constant_all<T_y, T_loc, T_scale>::value>((y_val - mu_val)
70 const auto& exp_m_scaled_diff
71 = to_ref_if<!is_constant_all<T_y, T_loc, T_scale>::value>(
73 const auto& cdf_n = to_ref_if<!is_constant_all<T_y, T_loc, T_scale>::value>(
74 exp(-exp_m_scaled_diff));
76 T_partials_return cdf(1.0);
79 cdf = forward_as<T_partials_array>(cdf_n).prod();
81 cdf = forward_as<T_partials_return>(cdf_n);
85 const auto& rep_deriv_tmp =
exp(-scaled_diff - exp_m_scaled_diff);
87 = to_ref_if<!is_constant_all<T_loc>::value
90 >= 2>(cdf * rep_deriv_tmp / (beta_val * cdf_n));
92 partials<0>(ops_partials) = rep_deriv;
95 partials<1>(ops_partials) = -rep_deriv;
98 partials<2>(ops_partials) = -rep_deriv * scaled_diff;
101 return ops_partials.build(cdf);
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 > gumbel_cdf(const T_y_cl &y, const T_loc_cl &mu, const T_scale_cl &beta)
Returns the gumbel cumulative distribution function for the given location, and scale.
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
bool size_zero(const T &x)
Returns 1 if input is of length 0, returns 0 otherwise.
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.
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
void check_finite(const char *function, const char *name, const T_y &y)
Return true if all values in y are finite.
void check_not_nan(const char *function, const char *name, const T_y &y)
Check if y is not NaN.
void check_positive(const char *function, const char *name, const T_y &y)
Check if y is positive.
fvar< T > beta(const fvar< T > &x1, const fvar< T > &x2)
Return fvar with the beta function applied to the specified arguments and its gradient.
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
fvar< T > exp(const fvar< T > &x)
typename ref_type_if<!is_constant< T >::value, 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 ...
If the input type T is either an eigen matrix with 1 column or 1 row at compile time or a standard ve...
Extends std::true_type when instantiated with zero or more template parameters, all of which extend t...