pred.block

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

pred.block function

<dl><dt>Y</dt>
<dd>data for prediction</dd>
<dt>phi</dt>
<dd>parameter matrix</dd>
<dt>q</dt>
<dd>lag</dd>
<dt>nob</dt>
<dd>total length of data</dd>
<dt>p</dt>
<dd>the dimension of time series components</dd>
<dt>h</dt>
<dd>the length of observation to predict</dd></dl>

Arguments

Prediction function (block) — pred.block

<dl>

<dt>Y</dt>
<dd>data for prediction</dd>


<dt>phi</dt>
<dd>parameter matrix</dd>


<dt>q</dt>
<dd>lag</dd>


<dt>nob</dt>
<dd>total length of data</dd>


<dt>p</dt>
<dd>the dimension of time series components</dd>


<dt>h</dt>
<dd>the length of observation to predict</dd>

</dl>

Prediction function (block)

pred.block: Prediction function (block)

Description

Usage

Value

Arguments