1#ifndef STAN_MATH_PRIM_PROB_PARETO_TYPE_2_LCDF_HPP
2#define STAN_MATH_PRIM_PROB_PARETO_TYPE_2_LCDF_HPP
21template <
typename T_y,
typename T_loc,
typename T_scale,
typename T_shape,
23 T_y, T_loc, T_scale, T_shape>* =
nullptr>
25 const T_y& y,
const T_loc& mu,
const T_scale& lambda,
26 const T_shape& alpha) {
33 static constexpr const char* function =
"pareto_type_2_lcdf";
35 mu,
"Scale parameter", lambda,
"Shape parameter",
44 T_lambda_ref lambda_ref = lambda;
45 T_alpha_ref alpha_ref = alpha;
49 decltype(
auto) lambda_val
58 const auto& temp = to_ref_if<!is_constant_all<T_shape>::value>(
59 1 + (y_val - mu_val) / lambda_val);
60 const auto& p1_pow_alpha
61 = to_ref_if<!is_constant_all<T_y, T_loc, T_scale, T_shape>::value>(
62 pow(temp, alpha_val));
63 T_partials_return P =
sum(
log1m(1 / p1_pow_alpha));
69 const auto& inv_p1_pow_alpha_minus_one
72 inv(p1_pow_alpha - 1));
77 >= 2>(alpha_val * inv_p1_pow_alpha_minus_one
78 / (lambda_val - mu_val + y_val));
80 partials<1>(ops_partials) = -grad_1_2;
83 edge<2>(ops_partials).partials_
84 = (mu_val - y_val) * grad_1_2 / lambda_val;
87 partials<0>(ops_partials) = std::move(grad_1_2);
91 partials<3>(ops_partials) =
log(temp) * inv_p1_pow_alpha_minus_one;
95 return ops_partials.build(P);
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, T_shape_cl > pareto_type_2_lcdf(const T_y_cl &y, const T_loc_cl &mu, const T_scale_cl &lambda, const T_shape_cl &alpha)
Returns the pareto type 2 log cumulative density function.
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
void check_nonnegative(const char *function, const char *name, const T_y &y)
Check if y is non-negative.
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.
auto pow(const T1 &x1, const T2 &x2)
fvar< T > log(const fvar< T > &x)
void check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low, Idxs... idxs)
Throw an exception if y is not greater or equal than low.
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.
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
fvar< T > log1m(const fvar< T > &x)
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.
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 ...
Extends std::true_type when instantiated with zero or more template parameters, all of which extend t...