detect.LpS: Single change point detection for low-rank plus sparse model...

In VARDetect: Multiple Change Point Detection in Structural VAR Models

Single change point detection for low-rank plus sparse model structure

Description

Single change point detection for low-rank plus sparse model using minimizing SSE method.

Usage

detect.LpS(data, lambda, mu, alpha_L, skip = 50)

Arguments

data	A n by p dataset, n is the number of observations, p is the number of variables
lambda	A 2-d vector recording tuning parameters for sparse components left/right
mu	A 2-d vector recording tuning parameters for low rank components left/right
alpha_L	A numeric value, a positive number indicating the constraint space for low rank matrix
skip	The number of observations at the boundaries we should skip

Value

A list object, which includes the followings:

cp

A vector recording all estimated change points

S_hat1

Estimated sparse component for the left-handed side

S_hat2

Estimated sparse component for the right-handed side

L_hat1

Estimated low rank component for the left-handed side

L_hat2

Estimated low rank component for the right-handed side

sse

The sum of squared errors for all passed time points

VARDetect documentation built on May 10, 2022, 9:07 a.m.