src/hierarchies/nnig_hierarchy.cc
//! \param data Column vector of data points
//! \return     Marginal distribution vector evaluated in data (log)
\param data Column vector of data points
\return     Marginal distribution vector evaluated in data (log)
\ param data Column vector of data points \ return Marginal distribution vector evaluated in data ( log )
double NNIGHierarchy::marg_lpdf(const Eigen::RowVectorXd &datum) const {
  double sig_n = sqrt(hypers->scale * (hypers->var_scaling + 1) /
                      (hypers->shape * hypers->var_scaling));
  return stan::math::student_t_lpdf(datum(0), 2 * hypers->shape, hypers->mean,
                                    sig_n);
}
double NNIGHierarchy :: marg_lpdf ( const Eigen :: RowVectorXd & datum ) const { double sig_n = sqrt ( hypers -> scale * ( hypers -> var_scaling + 1 ) / ( hypers -> shape * hypers -> var_scaling ) ) ; return stan :: math :: student_t_lpdf ( datum ( 0 ) , 2 * hypers -> shape , hypers -> mean , sig_n ) ; }
\param data Column vector of data points
\return     Marginal distribution vector evaluated in data (log)
\ param data Column vector of data points \ return Marginal distribution vector evaluated in data ( log )