Automatic Differentiation
 
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laplace_marginal_poisson_log_lpmf.hpp
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1#ifndef STAN_MATH_MIX_PROB_LAPLACE_MARGINAL_POISSON_LOG_LPMF_HPP
2#define STAN_MATH_MIX_PROB_LAPLACE_MARGINAL_POISSON_LOG_LPMF_HPP
3
15
16namespace stan {
17namespace math {
18
34 template <typename Theta, typename YVec, typename Mean,
36 inline auto operator()(const Theta& theta, const YVec& y,
37 const std::vector<int>& y_index, Mean&& mean,
38 std::ostream* /*pstream*/) const {
39 Eigen::VectorXd counts_per_group = Eigen::VectorXd::Zero(theta.size());
40 Eigen::VectorXd n_per_group = Eigen::VectorXd::Zero(theta.size());
41
42 for (int i = 0; i < theta.size(); i++) {
43 counts_per_group(y_index[i] - 1) += y[i];
44 n_per_group(y_index[i] - 1) += 1;
45 }
46
47 auto theta_offset = to_ref(add(theta, mean));
48
49 return -sum(lgamma(add(counts_per_group, 1)))
50 + dot_product(theta_offset, counts_per_group)
51 - dot_product(n_per_group, exp(theta_offset));
52 }
53};
54
76template <bool propto = false, typename Mean, typename CovarFun,
77 typename CovarArgs, typename OpsTuple>
79 const std::vector<int>& y, const std::vector<int>& y_index, Mean&& mean,
80 int hessian_block_size, CovarFun&& covariance_function,
81 CovarArgs&& covar_args, OpsTuple&& ops, std::ostream* msgs) {
82 auto options
83 = internal::tuple_to_laplace_options(std::forward<OpsTuple>(ops));
84 options.hessian_block_size = hessian_block_size;
87 std::forward_as_tuple(y, y_index, std::forward<Mean>(mean)),
88 covariance_function, std::forward<CovarArgs>(covar_args),
89 std::move(options), msgs);
90}
91
110template <bool propto = false, typename CovarFun, typename CovarArgs,
111 typename Mean>
113 const std::vector<int>& y, const std::vector<int>& y_index, Mean&& mean,
114 int hessian_block_size, CovarFun&& covariance_function,
115 CovarArgs&& covar_args, std::ostream* msgs) {
116 auto options = laplace_options_default{hessian_block_size};
119 std::forward_as_tuple(y, y_index, std::forward<Mean>(mean)),
120 covariance_function, std::forward<CovarArgs>(covar_args), options, msgs);
121}
122
123} // namespace math
124} // namespace stan
125
126#endif
require_t< is_eigen_vector< std::decay_t< T > > > require_eigen_vector_t
Require type satisfies is_eigen_vector.
addition_< as_operation_cl_t< T_a >, as_operation_cl_t< T_b > > add(T_a &&a, T_b &&b)
Reference for calculations of marginal and its gradients: Margossian et al (2020),...
constexpr auto tuple_to_laplace_options(Options &&ops)
scalar_type_t< T > mean(const T &m)
Returns the sample mean (i.e., average) of the coefficients in the specified std vector,...
Definition mean.hpp:20
auto laplace_marginal_density(LLFun &&ll_fun, LLTupleArgs &&ll_args, CovarFun &&covariance_function, CovarArgs &&covar_args, const laplace_options< InitTheta > &options, std::ostream *msgs)
For a latent Gaussian model with global parameters phi, latent variables theta, and observations y,...
auto laplace_marginal_tol_poisson_log_lpmf(const std::vector< int > &y, const std::vector< int > &y_index, Mean &&mean, int hessian_block_size, CovarFun &&covariance_function, CovarArgs &&covar_args, OpsTuple &&ops, std::ostream *msgs)
Wrapper function around the laplace_marginal function for a log poisson likelihood.
fvar< T > lgamma(const fvar< T > &x)
Return the natural logarithm of the gamma function applied to the specified argument.
Definition lgamma.hpp:21
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
Definition sum.hpp:23
ref_type_t< T && > to_ref(T &&a)
This evaluates expensive Eigen expressions.
Definition to_ref.hpp:18
auto laplace_marginal_poisson_log_lpmf(const std::vector< int > &y, const std::vector< int > &y_index, Mean &&mean, int hessian_block_size, CovarFun &&covariance_function, CovarArgs &&covar_args, std::ostream *msgs)
Wrapper function around the laplace_marginal function for a log poisson likelihood.
auto dot_product(const T_a &a, const T_b &b)
Returns the dot product of the specified vectors.
fvar< T > exp(const fvar< T > &x)
Definition exp.hpp:15
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
auto operator()(const Theta &theta, const YVec &y, const std::vector< int > &y_index, Mean &&mean, std::ostream *) const
Returns the lpmf for a Poisson with a log link across multiple groups.