1#ifndef STAN_MATH_PRIM_PROB_INV_GAMMA_LPDF_HPP
2#define STAN_MATH_PRIM_PROB_INV_GAMMA_LPDF_HPP
41template <
bool propto,
typename T_y,
typename T_shape,
typename T_scale,
43 T_y, T_shape, T_scale>* =
nullptr>
45 const T_y& y,
const T_shape& alpha,
const T_scale&
beta) {
50 static constexpr const char* function =
"inv_gamma_lpdf";
52 alpha,
"Scale parameter",
beta);
55 T_alpha_ref alpha_ref = alpha;
56 T_beta_ref beta_ref =
beta;
72 if (
sum(promote_scalar<int>(y_val <= 0))) {
76 T_partials_return logp(0);
80 = to_ref_if<include_summand<propto, T_y, T_shape>::value>(
log(y_val));
87 const auto& log_beta = to_ref_if<is_autodiff_v<T_shape>>(
log(beta_val));
89 if constexpr (is_autodiff_v<T_shape>) {
90 partials<1>(ops_partials) = log_beta -
digamma(alpha_val) - log_y;
94 logp -=
sum((alpha_val + 1.0) * log_y) * N /
max_size(y, alpha);
98 =
to_ref_if<(is_autodiff_v<T_y> || is_autodiff_v<T_scale>)>(
inv(y_val));
100 if constexpr (is_autodiff_v<T_y>) {
101 edge<0>(ops_partials).partials_
102 = (beta_val * inv_y - alpha_val - 1) * inv_y;
104 if constexpr (is_autodiff_v<T_scale>) {
105 partials<2>(ops_partials) = alpha_val / beta_val - inv_y;
108 return ops_partials.build(logp);
111template <
typename T_y,
typename T_shape,
typename T_scale>
113 const T_y& y,
const T_shape& alpha,
const T_scale&
beta) {
114 return inv_gamma_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_shape_cl, T_scale_cl > inv_gamma_lpdf(const T_y_cl &y, const T_shape_cl &alpha, const T_scale_cl &beta)
The log of an inverse gamma density for y with the specified shape 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>>.
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.
fvar< T > lgamma(const fvar< T > &x)
Return the natural logarithm of the gamma function applied to the specified argument.
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.
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 > digamma(const fvar< T > &x)
Return the derivative of the log gamma function at the specified argument.
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...