data.unrestricted

<code>set.seed(123)</code> 
<code>n &lt;- 500</code> 
<code>p &lt;- 50</code> 
<code>common &lt;- sim.unrestricted(n, p)</code> 
<code>idio &lt;- sim.var(n, p)</code> 
<code>x &lt;- common$data + idio$data</code>

datasets

Implements methods for network estimation and forecasting of high-dimensional time series
exhibiting strong serial and cross-sectional correlations under a factor-adjusted vector autoregressive model.
See Barigozzi, Cho and Owens (2024+) <doi:10.1080/07350015.2023.2257270> for further descriptions of FNETS methodology and
Owens, Cho and Barigozzi (2024+) <arXiv:2301.11675> accompanying the R package.

Haeran Cho

fnets

Factor-Adjusted Network Estimation and Forecasting for
High-Dimensional Time Series

Matteo Barigozzi

Dom Owens

data.unrestricted function

## `data.unrestricted`
A ts object with 500 rows (observations) and 50 columns (series)

Format

<code>set.seed(123)</code> 
<code>n &lt;- 500</code> 
<code>p &lt;- 50</code> 
<code>common &lt;- sim.unrestricted(n, p)</code> 
<code>idio &lt;- sim.var(n, p)</code> 
<code>x &lt;- common$data + idio$data</code>

data.unrestricted: Simulated data from the unrestricted factor-adjusted vector autoregression model

Description

Usage

Arguments

Format