FullRegression: FullRegression

In lorenzha/hdcd: High-Dimensional Changepoint Detection

Description

Neighbourhood selection for a given set of changepoints and a data sequence

Usage

FullRegression(x, cpts, lambda = 0.1, standardize = T, threshold = 1e-07)

Arguments

x	A n times p data matrix
cpts	A set of changepoints correspoding to row indices.
lambda	Sparsity penalty parameter.
standardize	Boolean. If TRUE the penalty parameter λ will be adjusted for every dimension in the single Lasso fits according to the standard deviation in the data.
threshold	The threshold for halting the iteration in glasso or glmnet. In the former it controls the absolute change of single parameters in the latter it controls the total objective value. This value is ignored if FUN is not NULL.

Value

est_coefs

A p times p matrix of estimated coefficients.

est_mean

A p vector of estimated means.

est_intercepts

A p vector of estimated intercepts.

lorenzha/hdcd documentation built on Sept. 2, 2018, 8:20 p.m.