predict.fm

Produces forecasts of the data input to <code>object</code> for a given forecasting horizon by
estimating the best linear predictors of the common component

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

predict.fm function

<dl><dt>object</dt>
<dd><code>fm</code> object</dd>
<dt>n.ahead</dt>
<dd>forecasting horizon</dd>
<dt>fc.restricted</dt>
<dd>if <code>fc.restricted = TRUE</code>, the forecast is generated under a restricted factor model</dd>
<dt>r</dt>
<dd>number of static factors, or a string specifying the factor number selection method when <code>fc.restricted = TRUE</code>;
possible values are:<dl>
 <dt><code>"ic"</code></dt>
<dd>information criteria of Alessi, Barigozzi &amp; Capasso (2010)</dd></dl></dd> <dt><code>"er"</code></dt>
<dd>eigenvalue ratio of Ahn &amp; Horenstein (2013)</dd>
</dl>
<dt>...</dt>
<dd>not used</dd>

Arguments

Forecasting for factor models — predict.fm

<dl>

<dt>object</dt>
<dd><code>fm</code> object</dd>


<dt>n.ahead</dt>
<dd>forecasting horizon</dd>


<dt>fc.restricted</dt>
<dd>if <code>fc.restricted = TRUE</code>, the forecast is generated under a restricted factor model</dd>


<dt>r</dt>
<dd>number of static factors, or a string specifying the factor number selection method when <code>fc.restricted = TRUE</code>;
possible values are:<dl>
 <dt><code>"ic"</code></dt>
<dd>information criteria of Alessi, Barigozzi &amp; Capasso (2010)</dd>

 <dt><code>"er"</code></dt>
<dd>eigenvalue ratio of Ahn &amp; Horenstein (2013)</dd>


</dl></dd>


<dt>...</dt>
<dd>not used</dd>

</dl>

predict.fm: Forecasting for factor models

Description

Usage

Value

Arguments

See Also

Examples