cmp::density Namespace Reference

Classes
class	KDE
	Multivariate Kernel Density Estimation (KDE) class. More...

Functions
Eigen::MatrixXd	bandwidthSelectionRule (const KDE::BandWidthSelectionMethod &method, Eigen::Ref< Eigen::MatrixXd > xObs)
	Computes the bandwidth matrix using standard rules of thumb.
void	bandwidthOptimizationCrossValidation (const cmp::statistics::KFold &kf, Eigen::Ref< Eigen::MatrixXd > xObs, std::shared_ptr< cmp::kernel::Kernel > kernel, std::shared_ptr< cmp::kernel::Bandwidth > initialBandwidth, const double &min, const double &max, nlopt::algorithm alg, const double &tol=1e-4)
	Optimizes the bandwidth matrix using K-Fold cross-validation over the observations.

Function Documentation

bandwidthOptimizationCrossValidation()

void cmp::density::bandwidthOptimizationCrossValidation	(	const cmp::statistics::KFold &	kf,
		Eigen::Ref< Eigen::MatrixXd >	xObs,
		std::shared_ptr< cmp::kernel::Kernel >	kernel,
		std::shared_ptr< cmp::kernel::Bandwidth >	initialBandwidth,
		const double &	min,
		const double &	max,
		nlopt::algorithm	alg,
		const double &	tol = 1e-4
	)

Optimizes the bandwidth matrix using K-Fold cross-validation over the observations.

Parameters

kf	KFold cross-validation partitioning helper.
xObs	Observation data matrix.
kernel	The density kernel to use.
initialBandwidth	Input/output bandwidth object to optimize.
min	Minimum bounds for bandwidth parameters.
max	Maximum bounds for bandwidth parameters.
alg	The optimization algorithm.
tol	Optimization relative tolerance.

bandwidthSelectionRule()

Eigen::MatrixXd cmp::density::bandwidthSelectionRule	(	const KDE::BandWidthSelectionMethod &	method,
		Eigen::Ref< Eigen::MatrixXd >	xObs
	)

Computes the bandwidth matrix using standard rules of thumb.

Parameters

method	Selection rule (SCOTT or SILVERMAN).
xObs	Observation data matrix.

Returns

Calculated bandwidth matrix.