shrinkage.lr

Shrinkage function for low-rank soft-thresholding

internal

Implementations of Thresholded Block Segmentation Scheme (TBSS) and Low-rank plus Sparse Two Step Procedure (LSTSP) algorithms for detecting multiple changes in structural VAR models. The package aims to address the problem of change point detection in piece-wise stationary VAR models, under different settings regarding the structure of their transition matrices (autoregressive dynamics); specifically, the following cases are included: (i) (weakly) sparse, (ii) structured sparse, and (iii) low rank plus sparse. It includes multiple algorithms and related extensions from Safikhani and Shojaie (2020) <doi:10.1080/01621459.2020.1770097> and Bai, Safikhani and Michailidis (2020) <doi:10.1109/TSP.2020.2993145>.

Yue Bai

VARDetect

Multiple Change Point Detection in Structural VAR Models

Peiliang Bai

Abolfazl Safikhani

George Michailidis

shrinkage.lr function

<dl><dt>y</dt>
<dd>A matrix, or a vector for thresholding</dd>
<dt>tau</dt>
<dd>A positive number, threshold</dd></dl>

Arguments

Shrinkage function for low-rank soft-thresholding — shrinkage.lr

<dl>

<dt>y</dt>
<dd>A matrix, or a vector for thresholding</dd>


<dt>tau</dt>
<dd>A positive number, threshold</dd>

</dl>

shrinkage.lr: Shrinkage function for low-rank soft-thresholding

Description

Usage

Value

Arguments