Automatic Differentiation
 
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cauchy_lccdf.hpp
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1#ifndef STAN_MATH_PRIM_PROB_CAUCHY_LCCDF_HPP
2#define STAN_MATH_PRIM_PROB_CAUCHY_LCCDF_HPP
3
14#include <cmath>
15
16namespace stan {
17namespace math {
18
34template <typename T_y, typename T_loc, typename T_scale,
36 T_y, T_loc, T_scale>* = nullptr>
38 const T_scale& sigma) {
39 using T_partials_return = partials_return_t<T_y, T_loc, T_scale>;
40 using T_y_ref = ref_type_t<T_y>;
41 using T_mu_ref = ref_type_t<T_loc>;
42 using T_sigma_ref = ref_type_t<T_scale>;
43 static constexpr const char* function = "cauchy_lccdf";
44 check_consistent_sizes(function, "Random variable", y, "Location parameter",
45 mu, "Scale Parameter", sigma);
46 T_y_ref y_ref = y;
47 T_mu_ref mu_ref = mu;
48 T_sigma_ref sigma_ref = sigma;
49 check_not_nan(function, "Random variable", y_ref);
50 check_finite(function, "Location parameter", mu_ref);
51 check_positive_finite(function, "Scale parameter", sigma_ref);
52
53 if (size_zero(y, mu, sigma)) {
54 return 0;
55 }
56
57 T_partials_return ccdf_log(0.0);
58 auto ops_partials = make_partials_propagator(y_ref, mu_ref, sigma_ref);
59
60 scalar_seq_view<T_y_ref> y_vec(y_ref);
61 scalar_seq_view<T_mu_ref> mu_vec(mu_ref);
62 scalar_seq_view<T_sigma_ref> sigma_vec(sigma_ref);
63 size_t N = max_size(y, mu, sigma);
64
65 for (size_t n = 0; n < N; n++) {
66 const T_partials_return y_dbl = y_vec.val(n);
67 const T_partials_return mu_dbl = mu_vec.val(n);
68 const T_partials_return sigma_inv_dbl = 1.0 / sigma_vec.val(n);
69 const T_partials_return sigma_dbl = sigma_vec.val(n);
70 const T_partials_return z = (y_dbl - mu_dbl) * sigma_inv_dbl;
71
72 const T_partials_return Pn = 0.5 - atan(z) / pi();
73 ccdf_log += log(Pn);
74
75 const T_partials_return rep_deriv
76 = 1.0 / (Pn * pi() * (z * z * sigma_dbl + sigma_dbl));
78 partials<0>(ops_partials)[n] -= rep_deriv;
79 }
81 partials<1>(ops_partials)[n] += rep_deriv;
82 }
84 partials<2>(ops_partials)[n] += rep_deriv * z;
85 }
86 }
87 return ops_partials.build(ccdf_log);
88}
89
90} // namespace math
91} // namespace stan
92#endif
scalar_seq_view provides a uniform sequence-like wrapper around either a scalar or a sequence of scal...
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 > cauchy_lccdf(const T_y_cl &y, const T_loc_cl &mu, const T_scale_cl &sigma)
Returns the cauchy log complementary cumulative distribution function for the given location,...
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.
Definition size_zero.hpp:19
fvar< T > log(const fvar< T > &x)
Definition log.hpp:18
void check_consistent_sizes(const char *)
Trivial no input case, this function is a no-op.
fvar< T > atan(const fvar< T > &x)
Definition atan.hpp:16
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.
static constexpr double pi()
Return the value of pi.
Definition constants.hpp:36
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
Definition max_size.hpp:20
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< true, T >::type ref_type_t
Definition ref_type.hpp:55
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...