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generalized_normal_test.hpp
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176 lines (149 loc) · 5.3 KB
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// Arguments: Doubles, Doubles, Doubles, Doubles
#include <stan/math/prim/prob/generalized_normal_lpdf.hpp>
#include <stan/math/prim/fun/abs.hpp>
#include <stan/math/prim/fun/log.hpp>
#include <stan/math/prim/fun/pow.hpp>
#include <stan/math/prim/fun/tgamma.hpp>
#include <stan/math/prim/fun/constants.hpp>
using std::numeric_limits;
using std::vector;
class AgradDistributionGeneralizedNormal : public AgradDistributionTest {
public:
void valid_values(vector<vector<double> >& parameters,
vector<double>& log_prob) {
vector<double> param(4);
param[0] = 0; // y
param[1] = 0; // mu
param[2] = 1; // alpha
param[3] = 2; // beta
parameters.push_back(param);
log_prob.push_back(
-0.57236494292470008707171367567652935582); // expected log_prob
param[0] = 1; // y
param[1] = 0; // mu
param[2] = 1; // alpha
param[3] = 2; // beta
parameters.push_back(param);
log_prob.push_back(
-1.5723649429247000870717136756765293558); // expected log_prob
param[0] = -2; // y
param[1] = 0; // mu
param[2] = 1; // alpha
param[3] = 2; // beta
parameters.push_back(param);
log_prob.push_back(
-4.5723649429247000870717136756765293558); // expected log_prob
param[0] = -3.5; // y
param[1] = 1.9; // mu
param[2] = 7.2; // alpha
param[3] = 2; // beta
parameters.push_back(param);
log_prob.push_back(
-3.1089459689467097140959090592117462617); // expected log_prob
param[0] = 0; // y
param[1] = 0; // mu
param[2] = 1; // alpha
param[3] = 1; // beta
parameters.push_back(param);
log_prob.push_back(
-0.69314718055994530941723212145817656808); // expected log_prob
param[0] = 1; // y
param[1] = 0; // mu
param[2] = 1; // alpha
param[3] = 1; // beta
parameters.push_back(param);
log_prob.push_back(
-1.6931471805599453094172321214581765681); // expected log_prob
param[0] = -2; // y
param[1] = 0; // mu
param[2] = 1; // alpha
param[3] = 1; // beta
parameters.push_back(param);
log_prob.push_back(
-2.6931471805599453094172321214581765681); // expected log_prob
param[0] = -3.5; // y
param[1] = 1.9; // mu
param[2] = 7.2; // alpha
param[3] = 1; // beta
parameters.push_back(param);
log_prob.push_back(
-3.4172282065819549364414275049933934740); // expected log_prob
param[0] = 0; // y
param[1] = 0; // mu
param[2] = 1; // alpha
param[3] = 1.5; // beta
parameters.push_back(param);
log_prob.push_back(
-0.59083234759930449611508182336583846717); // expected log_prob
param[0] = 1; // y
param[1] = 0; // mu
param[2] = 1; // alpha
param[3] = 1.5; // beta
parameters.push_back(param);
log_prob.push_back(
-1.5908323475993044961150818233658384672); // expected log_prob
param[0] = -2; // y
param[1] = 0; // mu
param[2] = 1; // alpha
param[3] = 1.5; // beta
parameters.push_back(param);
log_prob.push_back(
-3.4192594723454945937184592717852346243); // expected log_prob
param[0] = -3.5; // y
param[1] = 1.9; // mu
param[2] = 7.2; // alpha
param[3] = 1.5; // beta
parameters.push_back(param);
log_prob.push_back(
-3.2144324264596431082120695849657575107); // expected log_prob
}
void invalid_values(vector<size_t>& index, vector<double>& value) {
// y
// mu
index.push_back(1U);
value.push_back(numeric_limits<double>::infinity());
index.push_back(1U);
value.push_back(-numeric_limits<double>::infinity());
// alpha
index.push_back(2U);
value.push_back(0.0);
index.push_back(2U);
value.push_back(-1.0);
index.push_back(2U);
value.push_back(-numeric_limits<double>::infinity());
// beta
index.push_back(3U);
value.push_back(0.0);
index.push_back(3U);
value.push_back(-1.0);
index.push_back(3U);
value.push_back(-numeric_limits<double>::infinity());
}
template <typename T_y, typename T_loc, typename T_scale, typename T_shape,
typename T5, typename T6>
stan::return_type_t<T_y, T_loc, T_scale, T_shape> log_prob(
const T_y& y, const T_loc& mu, const T_scale& alpha, const T_shape& beta,
const T5&, const T6&) {
return stan::math::generalized_normal_lpdf(y, mu, alpha, beta);
}
template <bool propto, typename T_y, typename T_loc, typename T_scale,
typename T_shape, typename T5, typename T6>
stan::return_type_t<T_y, T_loc, T_scale, T_shape> log_prob(
const T_y& y, const T_loc& mu, const T_scale& alpha, const T_shape& beta,
const T5&, const T6&) {
return stan::math::generalized_normal_lpdf<propto>(y, mu, alpha, beta);
}
template <typename T_y, typename T_loc, typename T_scale, typename T_shape,
typename T5, typename T6>
stan::return_type_t<T_y, T_loc, T_scale, T_shape> log_prob_function(
const T_y& y, const T_loc& mu, const T_scale& alpha, const T_shape& beta,
const T5&, const T6&) {
using stan::math::abs;
using stan::math::inv;
using stan::math::lgamma;
using stan::math::log;
using stan::math::LOG_TWO;
return -LOG_TWO - log(alpha) - lgamma(1.0 + inv(beta))
- pow(abs(y - mu) / alpha, beta);
}
};