plot.gsmarpred

<code>plot.gsmarpred</code> is plot method for class 'gsmarpred' objects

Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR),
Student's t Mixture Autoregressive (StMAR), and Gaussian and Student's t Mixture Autoregressive (G-StMAR) models,
quantile residual tests, graphical diagnostics, forecast and simulate from GMAR, StMAR and G-StMAR processes.
Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) <doi:10.1111/jtsa.12108>,
Mika Meitz, Daniel Preve, Pentti Saikkonen (2023) <doi:10.1080/03610926.2021.1916531>,
Savi Virolainen (2022) <doi:10.1515/snde-2020-0060>.

Savi Virolainen

uGMAR

Estimate Univariate Gaussian and Student's t Mixture
Autoregressive Models

plot.gsmarpred function

<dl><dt>x</dt>
<dd>object of class <code>'gsmarpred'</code> created with <code>predict.gsmar</code>.</dd>
<dt>...</dt>
<dd>arguments passed to function <code>grid</code>.</dd>
<dt>nt</dt>
<dd>a positive integer specifying the number of observations to be plotted
along with the prediction. Default is <code>round(length(data)*0.15)</code>.</dd>
<dt>mix_weights</dt>
<dd><code>TRUE</code> if forecasts for mixing weights should be plotted, <code>FALSE</code> in not.</dd>
<dt>add_grid</dt>
<dd>should grid a be added to the plots?</dd></dl>

Arguments

Plot method for class 'gsmarpred' objects — plot.gsmarpred

<dl>

<dt>x</dt>
<dd>object of class <code>'gsmarpred'</code> created with <code>predict.gsmar</code>.</dd>


<dt>...</dt>
<dd>arguments passed to function <code>grid</code>.</dd>


<dt>nt</dt>
<dd>a positive integer specifying the number of observations to be plotted
along with the prediction. Default is <code>round(length(data)*0.15)</code>.</dd>


<dt>mix_weights</dt>
<dd><code>TRUE</code> if forecasts for mixing weights should be plotted, <code>FALSE</code> in not.</dd>


<dt>add_grid</dt>
<dd>should grid a be added to the plots?</dd>

</dl>

plot.gsmarpred: Plot method for class 'gsmarpred' objects

Description

Usage

Arguments

Details