1#ifndef STAN_MATH_OPENCL_PRIM_NEG_BINOMIAL_2_LOG_LPMF_HPP
2#define STAN_MATH_OPENCL_PRIM_NEG_BINOMIAL_2_LOG_LPMF_HPP
36template <
bool propto,
typename T_n_cl,
typename T_log_location_cl,
37 typename T_precision_cl,
39 T_n_cl, T_log_location_cl, T_precision_cl>* =
nullptr,
41 T_precision_cl>* =
nullptr>
42inline return_type_t<T_n_cl, T_log_location_cl, T_precision_cl>
44 const T_precision_cl& phi) {
45 static constexpr const char* function =
"neg_binomial_2_log_lpmf(OpenCL)";
46 using T_partials_return
52 "Log location parameter", eta,
"Precision parameter",
54 const size_t N =
max_size(n, eta, phi);
59 T_precision_cl>::value) {
66 const auto& eta_val =
value_of(eta_col);
67 const auto& phi_val =
value_of(phi_col);
69 auto check_n_nonnegative
70 =
check_cl(function,
"Failures variable", n,
"nonnegative");
71 auto n_nonnegative = n >= 0;
73 =
check_cl(function,
"Log location parameter", eta_val,
"finite");
75 auto check_phi_positive_finite
76 =
check_cl(function,
"Precision parameter", phi_val,
"positive finite");
77 auto phi_positive_finite = 0 < phi_val &&
isfinite(phi_val);
79 auto log_phi =
log(phi_val);
80 auto exp_eta =
exp(eta_val);
81 auto exp_eta_over_exp_eta_phi
83 auto log1p_exp_eta_m_logphi =
log1p_exp(eta_val - log_phi);
84 auto n_plus_phi = n + phi_val;
86 auto logp1 = -
elt_multiply(phi_val, log1p_exp_eta_m_logphi)
88 auto logp2 = static_select<include_summand<propto, T_precision_cl>::value>(
94 auto eta_deriv = n -
elt_multiply(n_plus_phi, exp_eta_over_exp_eta_phi);
95 auto phi_deriv = exp_eta_over_exp_eta_phi -
elt_divide(n, exp_eta + phi_val)
96 - log1p_exp_eta_m_logphi -
digamma(phi_val)
103 results(check_n_nonnegative, check_eta_finite, check_phi_positive_finite,
104 logp_cl, eta_deriv_cl, phi_deriv_cl)
105 =
expressions(n_nonnegative, eta_finite, phi_positive_finite, logp_expr,
114 partials<0>(ops_partials) = std::move(eta_deriv_cl);
117 partials<1>(ops_partials) = std::move(phi_deriv_cl);
119 return ops_partials.build(logp);
Represents an arithmetic matrix on the OpenCL device.
elt_multiply_< as_operation_cl_t< T_a >, as_operation_cl_t< T_b > > elt_multiply(T_a &&a, T_b &&b)
isfinite_< as_operation_cl_t< T > > isfinite(T &&a)
auto check_cl(const char *function, const char *var_name, T &&y, const char *must_be)
Constructs a check on opencl matrix or expression.
results_cl< T_results... > results(T_results &&... results)
Deduces types for constructing results_cl object.
binomial_coefficient_log_< as_operation_cl_t< T1 >, as_operation_cl_t< T2 > > binomial_coefficient_log(T1 &&a, T2 &&b)
auto as_column_vector_or_scalar(T &&a)
as_column_vector_or_scalar of a kernel generator expression.
elt_divide_< as_operation_cl_t< T_a >, as_operation_cl_t< T_b > > elt_divide(T_a &&a, T_b &&b)
calc_if_< true, as_operation_cl_t< T > > calc_if(T &&a)
auto colwise_sum(T &&a)
Column wise sum - reduction of a kernel generator expression.
expressions_cl< T_expressions... > expressions(T_expressions &&... expressions)
Deduces types for constructing expressions_cl object.
return_type_t< T_n_cl, T_log_location_cl, T_precision_cl > neg_binomial_2_log_lpmf(const T_n_cl &n, const T_log_location_cl &eta, const T_precision_cl &phi)
The log of the log transformed negative binomial density for the specified scalars given the specifie...
auto from_matrix_cl(const T &src)
Copies the source matrix that is stored on the OpenCL device to the destination Eigen matrix.
require_all_t< is_prim_or_rev_kernel_expression< std::decay_t< Types > >... > require_all_prim_or_rev_kernel_expression_t
Require type satisfies is_prim_or_rev_kernel_expression.
require_any_not_t< is_stan_scalar< std::decay_t< Types > >... > require_any_not_stan_scalar_t
Require at least one of the types do not satisfy is_stan_scalar.
T value_of(const fvar< T > &v)
Return the value of the specified variable.
fvar< T > log(const fvar< T > &x)
T1 static_select(T1 &&a, T2 &&b)
Returns one of the arguments that can be of different type, depending on the compile time condition.
fvar< T > log1p_exp(const fvar< T > &x)
void check_consistent_sizes(const char *)
Trivial no input case, this function is a no-op.
auto sum(const std::vector< T > &m)
Return the sum of the entries of the specified standard vector.
int64_t max_size(const T1 &x1, const Ts &... xs)
Calculate the size of the largest input.
auto make_partials_propagator(Ops &&... ops)
Construct an partials_propagator.
fvar< T > digamma(const fvar< T > &x)
Return the derivative of the log gamma function at the specified argument.
fvar< T > exp(const fvar< T > &x)
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 ...
bool isnan(const stan::math::var &a)
Checks if the given number is NaN.
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...