Detailed Description

Solver Policy 1 (Block): Cholesky decomposition using block W.

This solver is used when hessian_block_size > 1. It computes the block-diagonal negative Hessian of the log-likelihood, computes its principal square root via block_matrix_sqrt, and forms the system matrix B = I + W_r * Sigma * W_r for Cholesky factorization.

The sparse structure of W_r is initialized in the constructor to match the problem dimensions.

Note: This solver corresponds to solver == 1 with hessian_block_size > 1.

Definition at line 582 of file laplace_marginal_density_estimator.hpp.

#include <laplace_marginal_density_estimator.hpp>

Public Member Functions
template<typename NewtonStateT >
	CholeskyWSolverBlock (const NewtonStateT &state, int hessian_block_size)

template<typename NewtonStateT , typename LLFun , typename LLTupleArgs , typename CovarMat >
void	solve_step (NewtonStateT &state, const LLFun &ll_fun, const LLTupleArgs &ll_args, const CovarMat &covariance, int hessian_block_size, std::ostream *msgs)
	Perform one Newton step using block-diagonal Hessian solver.

double	compute_log_determinant () const
	Compute log determinant of B from Cholesky factor.

template<typename NewtonStateT >
auto	build_result (NewtonStateT &state, double log_det)
	Build the final result structure.

Public Attributes
Eigen::SparseMatrix< double >	W_r
	Sparse square root of block Hessian.

Eigen::SparseMatrix< double >	W_block
	Sparse block-diagonal Hessian from likelihood.

Eigen::LLT< Eigen::MatrixXd >	llt_B
	Cholesky factorization of B = I + W_r * Sigma * W_r.

The documentation for this struct was generated from the following file:

stan/math/mix/functor/laplace_marginal_density_estimator.hpp

Detailed Description

Public Member Functions

Public Attributes