f.func

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

f.func function

<dl><dt>x</dt>
<dd>Model parameters</dd>
<dt>A</dt>
<dd>Design matrix with size of n by p</dd>
<dt>b</dt>
<dd>Correspond vector or matrix</dd></dl>

Arguments

Main loss function for quardratic loss — f.func

<dl>

<dt>x</dt>
<dd>Model parameters</dd>


<dt>A</dt>
<dd>Design matrix with size of n by p</dd>


<dt>b</dt>
<dd>Correspond vector or matrix</dd>

</dl>

Main loss function for quardratic loss

f.func: Main loss function for quardratic loss

Description

Usage

Value

Arguments