An implementation of the coordinate descent step in the hybrid algorithm for solving SLOPE. More...

#include "../clusters.h"
#include "../math.h"
#include "slope_threshold.h"
#include <Eigen/Core>
#include <iostream>
#include <vector>

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Namespaces
namespace	slope
	Namespace containing SLOPE regression implementation.

Functions
template<typename T >
std::pair< double, double >	slope::computeGradientAndHessian (const T &x, const int k, const Eigen::VectorXd &w, const Eigen::VectorXd &residual, const Eigen::VectorXd &x_centers, const Eigen::VectorXd &x_scales, const double s, const JitNormalization jit_normalization, const int n)

std::pair< double, double >	slope::computeClusterGradientAndHessian (const Eigen::MatrixXd &x, const int j, const std::vector< int > &s, const Clusters &clusters, const Eigen::VectorXd &w, const Eigen::VectorXd &residual, const Eigen::VectorXd &x_centers, const Eigen::VectorXd &x_scales, const JitNormalization jit_normalization)

std::pair< double, double >	slope::computeClusterGradientAndHessian (const Eigen::SparseMatrix< double > &x, const int j, const std::vector< int > &s, const Clusters &clusters, const Eigen::VectorXd &w, const Eigen::VectorXd &residual, const Eigen::VectorXd &x_centers, const Eigen::VectorXd &x_scales, const JitNormalization jit_normalization)

template<typename T >
void	slope::coordinateDescent (Eigen::VectorXd &beta0, Eigen::VectorXd &beta, Eigen::VectorXd &residual, Clusters &clusters, const Eigen::ArrayXd &lambda, const T &x, const Eigen::VectorXd &w, const Eigen::VectorXd &x_centers, const Eigen::VectorXd &x_scales, const bool intercept, const JitNormalization jit_normalization, const bool update_clusters)

Detailed Description

An implementation of the coordinate descent step in the hybrid algorithm for solving SLOPE.

Definition in file hybrid_cd.h.

Namespaces