1#ifndef STAN_MATH_PRIM_PROB_PARETO_TYPE_2_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_PARETO_TYPE_2_LPDF_HPP
23template <
bool propto,
typename T_y,
typename T_loc,
typename T_scale,
26 T_y, T_loc, T_scale, T_shape>* =
nullptr>
28 const T_y& y,
const T_loc& mu,
const T_scale& lambda,
29 const T_shape& alpha) {
35 static constexpr const char* function =
"pareto_type_2_lpdf";
37 mu,
"Scale parameter", lambda,
"Shape parameter",
46 T_lambda_ref lambda_ref = lambda;
47 T_alpha_ref alpha_ref = alpha;
51 decltype(
auto) lambda_val
63 const auto& log1p_scaled_diff = to_ref_if<!is_constant_all<T_shape>::value>(
64 log1p((y_val - mu_val) / lambda_val));
66 size_t N =
max_size(y, mu, lambda, alpha);
67 T_partials_return logp(0.0);
75 logp -=
sum((alpha_val + 1.0) * log1p_scaled_diff);
84 inv(lambda_val + y_val - mu_val));
85 const auto& alpha_div_sum
91 inv_sum + alpha_div_sum);
93 partials<0>(ops_partials) = -deriv_1_2;
96 partials<1>(ops_partials) = std::move(deriv_1_2);
100 edge<2>(ops_partials).partials_
101 = alpha_div_sum * (y_val - mu_val) / lambda_val - inv_sum;
105 partials<3>(ops_partials) =
inv(alpha_val) - log1p_scaled_diff;
108 return ops_partials.build(logp);
111template <
typename T_y,
typename T_loc,
typename T_scale,
typename T_shape>
113 const T_y& y,
const T_loc& mu,
const T_scale& lambda,
114 const T_shape& alpha) {
115 return pareto_type_2_lpdf<false>(y, mu, lambda, alpha);
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_lpdf(const T_y_cl &y, const T_loc_cl &mu, const T_scale_cl &lambda, const T_shape_cl &alpha)
Returns the log PMF of the Pareto type 2 distribution.
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)
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.
fvar< T > log1p(const fvar< T > &x)
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
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.
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...
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...