computeResiduals

Computes the residuals from a VAR model by subtracting the fitted values (obtained
from the estimated coefficient matrices) from the original time series data.

internal

Implements the algorithm introduced in Tian, Y., and Safikhani, A. (2024)
<doi:10.5705/ss.202024.0182>, "Sequential Change Point Detection in High-dimensional
Vector Auto-regressive Models". This package provides tools for detecting change points
in the transition matrices of VAR models, effectively identifying shifts in temporal
and cross-correlations within high-dimensional time series data.

Yuhan Tian

VARcpDetectOnline

Sequential Change Point Detection for High-Dimensional VAR
Models

Abolfazl Safikhani

computeResiduals function

<dl><dt>data</dt>
<dd>A numeric matrix of the original time series (observations in rows).</dd>
<dt>A</dt>
<dd>List. A list of VAR coefficient matrices (one for each lag).</dd></dl>

Arguments

Compute VAR Model Residuals — computeResiduals

<dl>

<dt>data</dt>
<dd>A numeric matrix of the original time series (observations in rows).</dd>


<dt>A</dt>
<dd>List. A list of VAR coefficient matrices (one for each lag).</dd>

</dl>

computeResiduals: Compute VAR Model Residuals

Description

Usage

Value

Arguments