psigmq

Function computes a diagonal matrix of dimension m+1 by m+1
with i-th entry is the estimated variance of residuals of segment i

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

psigmq function

<dl><dt>res</dt>
<dd>big residual vector of the model</dd>
<dt>b</dt>
<dd>Estimated date of changes</dd>
<dt>q</dt>
<dd>Number of <code>z</code> regressors</dd>
<dt>m</dt>
<dd>Number of breaks</dd>
<dt>nt</dt>
<dd>The size of <code>z</code> regressors</dd></dl>

Arguments

Construct diagonal matrix of estimated variance — psigmq

<dl>

<dt>res</dt>
<dd>big residual vector of the model</dd>


<dt>b</dt>
<dd>Estimated date of changes</dd>


<dt>q</dt>
<dd>Number of <code>z</code> regressors</dd>


<dt>m</dt>
<dd>Number of breaks</dd>


<dt>nt</dt>
<dd>The size of <code>z</code> regressors</dd>

</dl>

psigmq: Construct diagonal matrix of estimated variance

Description

Usage

Value

Arguments