bregress2

Simulate data from time-varying time series regression model with change points

Plug-in and difference-based long-run covariance matrix estimation for time series regression. Two applications of hypothesis testing are also provided. The first one is for testing for structural stability in coefficient functions. The second one is aimed at detecting long memory in time series regression. Lujia Bai and Weichi Wu (2024)<doi:10.3150/23-BEJ1680> Zhou Zhou and Wei Biao Wu(2010)<doi:10.1111/j.1467-9868.2010.00743.x> Jianqing Fan and Wenyang Zhang<doi:10.1214/aos/1017939139> Lujia Bai and Weichi Wu(2024)<doi:10.1093/biomet/asae013> Dimitris N. Politis, Joseph P. Romano, Michael Wolf(1999)<doi:10.1007/978-1-4612-1554-7> Weichi Wu and Zhou Zhou(2018)<doi:10.1214/17-AOS1582>.

Lujia Bai

mlrv

Long-Run Variance Estimation in Time Series Regression

Weichi Wu

bregress2 function

<dl><dt>nn</dt>
<dd>sample size</dd>
<dt>cp</dt>
<dd>number of change points. If cp is between 0 and 1, it specifies the location of the single change point</dd>
<dt>delta</dt>
<dd>double, magnitude of the jump</dd>
<dt>type</dt>
<dd>type of distributions of the innovations, default normal. It can also be "t4", "t5" and "t6".</dd></dl>

Arguments

Simulate data from time-varying time series regression model with change points — bregress2

<dl>

<dt>nn</dt>
<dd>sample size</dd>


<dt>cp</dt>
<dd>number of change points. If cp is between 0 and 1, it specifies the location of the single change point</dd>


<dt>delta</dt>
<dd>double, magnitude of the jump</dd>


<dt>type</dt>
<dd>type of distributions of the innovations, default normal. It can also be "t4", "t5" and "t6".</dd>

</dl>

bregress2: Simulate data from time-varying time series regression model with change points

Description

Usage

Value

Arguments