text: #include "_glm.h"
  
  namespace autowig
  {
      typedef ::statiskit::OptimizationEstimationImpl< double, class ::statiskit::glm::NegativeBinomialRegression, ::statiskit::DiscreteUnivariateConditionalDistributionEstimation >::Estimator class_type;
  
      class Trampoline : public class_type
      {
          public:
              using ::statiskit::OptimizationEstimationImpl< double, class ::statiskit::glm::NegativeBinomialRegression, ::statiskit::DiscreteUnivariateConditionalDistributionEstimation >::Estimator::Estimator;
  
              typedef class ::std::unique_ptr< struct ::statiskit::UnivariateConditionalDistributionEstimation::Estimator, struct ::std::default_delete< struct ::statiskit::UnivariateConditionalDistributionEstimation::Estimator > >  return_type_e0fab2db391a546591b690a17ebe80ff;
              virtual return_type_e0fab2db391a546591b690a17ebe80ff copy() const override { PYBIND11_OVERLOAD_PURE_UNIQUE_PTR(return_type_e0fab2db391a546591b690a17ebe80ff, class_type, copy, ); };
              typedef class ::std::unique_ptr< struct ::statiskit::UnivariateConditionalDistributionEstimation, struct ::std::default_delete< struct ::statiskit::UnivariateConditionalDistributionEstimation > >  return_type_bdacedd56eba5861a3003ac87a422cf6;
              typedef ::statiskit::UnivariateConditionalDistributionEstimation::data_type const & param_bdacedd56eba5861a3003ac87a422cf6_0_type;
              typedef bool const & param_bdacedd56eba5861a3003ac87a422cf6_1_type;
              virtual return_type_bdacedd56eba5861a3003ac87a422cf6 operator()(param_bdacedd56eba5861a3003ac87a422cf6_0_type param_0, param_bdacedd56eba5861a3003ac87a422cf6_1_type param_1) const override { PYBIND11_OVERLOAD_PURE_UNIQUE_PTR(return_type_bdacedd56eba5861a3003ac87a422cf6, class_type, operator(), param_0, param_1); };
              typedef ::uintptr_t  return_type_ed723b56ee6d50838db979e102419f39;
              virtual return_type_ed723b56ee6d50838db979e102419f39 identifier() const override { PYBIND11_OVERLOAD(return_type_ed723b56ee6d50838db979e102419f39, class_type, identifier, ); };
              typedef class ::std::unordered_set< statiskit::Index, struct ::std::hash< statiskit::Index >, struct ::std::equal_to< statiskit::Index >, class ::std::allocator< statiskit::Index > >  return_type_7ba100805cd95f1cba468c9ce84eb72c;
              virtual return_type_7ba100805cd95f1cba468c9ce84eb72c children() const override { PYBIND11_OVERLOAD(return_type_7ba100805cd95f1cba468c9ce84eb72c, class_type, children, ); };
      };
  
      class Publicist : public class_type
      {
          public:
              using class_type::identifier;
              using class_type::children;
      };
  }
  
  
  namespace autowig {
  }
  
  void wrapper_5cd9055473e258e1a98d3e1a52488fdc(pybind11::module& module)
  {
  
      pybind11::class_<class ::statiskit::OptimizationEstimationImpl< double, class ::statiskit::glm::NegativeBinomialRegression, struct ::statiskit::DiscreteUnivariateConditionalDistributionEstimation >::Estimator, autowig::Trampoline, autowig::HolderType< class ::statiskit::OptimizationEstimationImpl< double, class ::statiskit::glm::NegativeBinomialRegression, struct ::statiskit::DiscreteUnivariateConditionalDistributionEstimation >::Estimator >::Type, class ::statiskit::Optimization< struct ::statiskit::DiscreteUnivariateConditionalDistributionEstimation::Estimator > > class_5cd9055473e258e1a98d3e1a52488fdc(module, "Estimator", "");
      class_5cd9055473e258e1a98d3e1a52488fdc.def(pybind11::init<  >());
  
  }