correct

<code>hac()</code> corrects the estimated errors based on options of prewhitening
using a AR(1) process estimation of error terms to obtain
heteroskedasticy and autocorrelation consistency (HAC) errors with automatic
bandwith and kernel similar to Andrews, 1994

Functions provide comprehensive treatments for estimating, inferring, testing and model selecting in linear regression models with structural breaks. The tests, estimation methods, inference and information criteria implemented are discussed in Bai and Perron (1998) "Estimating and Testing Linear Models with Multiple Structural Changes" <doi:10.2307/2998540>.

Linh Nguyen

mbreaks

Estimation and Inference for Structural Breaks in Linear
Regression Models

Yohei Yamamoto

Pierre Perron

correct function

<dl><dt>reg</dt>
<dd>matrix of regressors</dd>
<dt>res</dt>
<dd>matrix of estimated residuals</dd>
<dt>prewhit</dt>
<dd>Option of using prewhitening process. If <code>1</code>, an AR(1)
process will be used to filter. If <code>0</code>, skipped the filtering process</dd></dl>

Arguments

Heteroskedasticy and autocorrelation consistency correction for residuals — correct

<dl>

<dt>reg</dt>
<dd>matrix of regressors</dd>


<dt>res</dt>
<dd>matrix of estimated residuals</dd>


<dt>prewhit</dt>
<dd>Option of using prewhitening process. If <code>1</code>, an AR(1)
process will be used to filter. If <code>0</code>, skipped the filtering process</dd>

</dl>

correct: Heteroskedasticy and autocorrelation consistency correction for residuals

Description

Usage

Value

Arguments