1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_LOG_HPP 2 #define STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_LOG_HPP 19 #include <boost/random/chi_squared_distribution.hpp> 20 #include <boost/random/variate_generator.hpp> 45 template <
bool propto,
46 typename T_y,
typename T_dof>
49 static const char*
function(
"chi_square_log");
57 T_partials_return logp(0.0);
63 "Degrees of freedom parameter", nu);
69 for (
size_t n = 0; n <
length(y); n++)
81 T_partials_return, T_y> log_y(
length(y));
82 for (
size_t i = 0; i <
length(y); i++)
87 T_partials_return, T_y> inv_y(
length(y));
88 for (
size_t i = 0; i <
length(y); i++)
93 T_partials_return, T_dof> lgamma_half_nu(
length(nu));
95 T_partials_return, T_dof>
96 digamma_half_nu_over_two(
length(nu));
98 for (
size_t i = 0; i <
length(nu); i++) {
99 T_partials_return half_nu = 0.5 *
value_of(nu_vec[i]);
101 lgamma_half_nu[i] =
lgamma(half_nu);
103 digamma_half_nu_over_two[i] =
digamma(half_nu) * 0.5;
108 for (
size_t n = 0; n < N; n++) {
109 const T_partials_return y_dbl =
value_of(y_vec[n]);
110 const T_partials_return half_y = 0.5 * y_dbl;
111 const T_partials_return nu_dbl =
value_of(nu_vec[n]);
112 const T_partials_return half_nu = 0.5 * nu_dbl;
116 logp += (half_nu-1.0) * log_y[n];
121 operands_and_partials.
d_x1[n] += (half_nu-1.0)*inv_y[n] - 0.5;
125 - digamma_half_nu_over_two[n] + log_y[n]*0.5;
128 return operands_and_partials.
value(logp);
131 template <
typename T_y,
typename T_dof>
135 return chi_square_log<false>(y, nu);
VectorView< T_return_type, false, true > d_x2
fvar< T > lgamma(const fvar< T > &x)
Return the natural logarithm of the gamma function applied to the specified argument.
T value_of(const fvar< T > &v)
Return the value of the specified variable.
fvar< T > log(const fvar< T > &x)
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
size_t length(const std::vector< T > &x)
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
void check_nonnegative(const char *function, const char *name, const T_y &y)
Check if y is non-negative.
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
void check_positive_finite(const char *function, const char *name, const T_y &y)
Check if y is positive and finite.
void check_not_nan(const char *function, const char *name, const T_y &y)
Check if y is not NaN.
return_type< T_y, T_dof >::type chi_square_log(const T_y &y, const T_dof &nu)
The log of a chi-squared density for y with the specified degrees of freedom parameter.
This class builds partial derivatives with respect to a set of operands.
size_t max_size(const T1 &x1, const T2 &x2)
VectorBuilder allocates type T1 values to be used as intermediate values.
const double NEG_LOG_TWO_OVER_TWO
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
void check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Check if the dimension of x1 is consistent with x2.
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
VectorView< T_return_type, false, true > d_x1
fvar< T > digamma(const fvar< T > &x)
Return the derivative of the log gamma function at the specified argument.