STSLIB::StsCovEstimators Class Reference

Covariance matrix estimators including shrinkage methods. More...

#include <sts_cov_estimators.h>

Static Public Member Functions
static std::pair< Eigen::MatrixXd, double >	ledoitWolf (const Eigen::MatrixXd &matData)
	Ledoit-Wolf optimal shrinkage covariance estimator.

Detailed Description

Covariance matrix estimators including shrinkage methods.

Covariance matrix estimators.

Definition at line 68 of file sts_cov_estimators.h.

Member Function Documentation

ledoitWolf()

std::pair< MatrixXd, double > StsCovEstimators::ledoitWolf ( const Eigen::MatrixXd & matData )

static

Ledoit-Wolf optimal shrinkage covariance estimator.

Computes the shrinkage coefficient analytically using the formula from Ledoit & Wolf (2004) "A well-conditioned estimator for large-dimensional covariance matrices" (Journal of Multivariate Analysis, 88(2), 365-411).

Parameters

[in]

matData

Zero-mean data, n_channels x n_samples.

Returns

std::pair containing the shrunk covariance matrix (n_channels x n_channels) and the shrinkage coefficient alpha in [0,1].

Definition at line 58 of file sts_cov_estimators.cpp.

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The documentation for this class was generated from the following files:

• src/libraries/sts/sts_cov_estimators.h
• src/libraries/sts/sts_cov_estimators.cpp