cv.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 with cross-validation

Description

single change point detection with cross-validation

Usage

cv.detect.LpS(
  data,
  lambda.1.seq = NULL,
  mu.1.seq = NULL,
  alpha_L = 0.25,
  skip = 50,
  nfold = 5
)

Arguments

data	a n by p datatset matrix
lambda.1.seq	a numeric vector, the sequence of tuning parameter for sparse component for the left segment
mu.1.seq	a numeric vector, the sequence of tuning parameter for low rank component for the left segment
alpha_L	a numeric value, indicates the constraint space of low rank component
skip	a positive integer, indicates the number of time points should be skipped close to the boundary
nfold	a positive integer, the number of folds for cross validation

Value

A list object, including

cp

Estimated change point

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 June 22, 2024, 10 a.m.