laplace_base_rng()

template<bool ReturnMeanAndCovCholesky = false, typename LLFunc , typename LLArgs , typename CovarFun , typename CovarArgs , bool InitTheta, typename RNG , require_t< is_all_arithmetic_scalar< CovarArgs, LLArgs > > * = nullptr>

auto stan::math::laplace_base_rng ( LLFunc &&  ll_fun, LLArgs &&  ll_args, CovarFun &&  covariance_function, CovarArgs &&  covar_args, const laplace_options< InitTheta > &  options, RNG &  rng, std::ostream *  msgs  )

inline

In a latent gaussian model,.

theta ~ Normal(theta | 0, Sigma(phi, x)) y ~ pi(y | theta, eta)

By default, returns a multivariate normal random variate sampled from the Laplace approximation of p(theta_pred | y, phi, x_pred). If ReturnMeanAndCovCholesky is true, instead of drawing a sample this returns the posterior mean and the Cholesky factor of the posterior covariance of that same Laplace approximation, as a std::tuple<Eigen::VectorXd, Eigen::MatrixXd>. Note that while the data is observed at x (train_tuple), the new samples are drawn for covariates x_pred (pred_tuple). To sample the "original" theta's, set pred_tuple = train_tuple.

Template Parameters

ReturnMeanAndCovCholesky	If false (default), draw and return a random variate from the approximate posterior. If true, return a tuple containing the posterior mean and the lower-triangular Cholesky factor of the posterior covariance instead of a sample.
LLFunc	Type of likelihood function.
LLArgs	Tuple of arguments types of likelihood function.
CovarFun	A functor with an operator()(CovarArgsElements..., {TrainTupleElements...| PredTupleElements...}) method. The operator() method should accept as arguments the inner elements of CovarArgs. The return type of the operator() method should be a type inheriting from Eigen::EigenBase with dynamic sized rows and columns.
CovarArgs	A tuple of types to passed as the first arguments of CovarFun::operator()
OpsTuple	A tuple of laplace_options types
RNG	A valid boost rng type

Parameters

	ll_fun	Likelihood function.
	ll_args	Arguments for likelihood function.
[in]	covariance_function	a function which returns the prior covariance.
[in]	covar_args	arguments for the covariance function.
	options	Control parameter for optimizer underlying Laplace approx.
[in,out]	rng	Random number generator
[in,out]	msgs	stream for messages from likelihood and covariance

Definition at line 47 of file laplace_base_rng.hpp.