1#ifndef STAN_MATH_PRIM_PROB_UNIFORM_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_UNIFORM_LPDF_HPP
44template <
bool propto,
typename T_y,
typename T_low,
typename T_high,
46 T_y, T_low, T_high>* =
nullptr>
54 static constexpr const char* function =
"uniform_lpdf";
56 "Lower bound parameter", alpha,
57 "Upper bound parameter",
beta);
60 T_alpha_ref alpha_ref = alpha;
61 T_beta_ref beta_ref =
beta;
68 check_finite(function,
"Lower bound parameter", alpha_val);
69 check_finite(function,
"Upper bound parameter", beta_val);
70 check_greater(function,
"Upper bound parameter", beta_val, alpha_val);
78 if (
sum(promote_scalar<int>(y_val < alpha_val))
79 ||
sum(promote_scalar<int>(beta_val < y_val))) {
83 T_partials_return logp = 0;
91 if constexpr (is_any_autodiff_v<T_low, T_high>) {
92 auto inv_beta_minus_alpha
93 =
to_ref_if<(is_autodiff_v<T_high> && is_autodiff_v<T_low>)>(
94 inv(beta_val - alpha_val));
95 if constexpr (is_autodiff_v<T_high>) {
98 partials<2>(ops_partials) = -inv_beta_minus_alpha *
math::size(y);
100 partials<2>(ops_partials) = -inv_beta_minus_alpha;
103 if constexpr (is_autodiff_v<T_low>) {
106 partials<1>(ops_partials) = inv_beta_minus_alpha *
math::size(y);
108 partials<1>(ops_partials) = std::move(inv_beta_minus_alpha);
113 return ops_partials.build(logp);
116template <
typename T_y,
typename T_low,
typename T_high>
119 const T_high&
beta) {
120 return uniform_lpdf<false>(y, alpha,
beta);
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_low_cl, T_high_cl > uniform_lpdf(const T_y_cl &y, const T_low_cl &alpha, const T_high_cl &beta)
The log of a uniform density for the given y, lower, and upper bound.
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>>.
static constexpr double LOG_ZERO
The natural logarithm of 0, .
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)
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.
void check_not_nan(const char *function, const char *name, const T_y &y)
Check if y is not NaN.
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 > beta(const fvar< T > &x1, const fvar< T > &x2)
Return fvar with the beta function applied to the specified arguments and its gradient.
void check_greater(const char *function, const char *name, const T_y &y, const T_low &low, Idxs... idxs)
Throw an exception if y is not strictly greater than low.
fvar< T > inv(const fvar< T > &x)
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
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 ...
If the input type T is either an eigen matrix with 1 column or 1 row at compile time or a standard ve...
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...