MixVAR-class

Mixture vector autoregressive models

classes

MixVAR

Model time series using mixture autoregressive (MAR)
models. Implemented are frequentist (EM) and Bayesian
methods for estimation, prediction and model
evaluation. See Wong and Li (2002)
<doi:10.1111/1467-9868.00222>, Boshnakov (2009)
<doi:10.1016/j.spl.2009.04.009>), and the extensive
references in the documentation.

Georgi Boshnakov

mixAR

Mixture Autoregressive Models

Davide Ravagli

MixVAR-class function

A virtual Class: No objects may be created from it.
Derived classes add distribution properties, e.g. use class
 <code>"MixVARGaussian"</code> for MixVAR models with Gaussian
 error components.

Objects from the Class

<dl>
 <dt><code>prob</code>:</dt>
<dd>the mixing probabilities,
 an object of class <code>"numeric"</code></dd> <dt><code>order</code>:</dt>
<dd>Object of class <code>"numeric"</code> ~~</dd> <dt><code>shift</code>:</dt>
<dd>Object of class <code>"matrix"</code> ~~</dd> <dt><code>vcov</code>:</dt>
<dd>Object of class <code>"array"</code> ~~</dd> <dt><code>arcoef</code>:</dt>
<dd>Object of class <code>"raggedCoefV"</code> ~~</dd> 
</dl>

Slots

<dl>
 <dt>fit_mixVAR</dt>
<dd><code>signature(x = "ANY", model = "MixAR")</code>: ...</dd> 
</dl>

Methods

Author

Class "MixVAR" --- mixture vector autoregressive models — MixVAR-class

<dl>
 <dt><code>prob</code>:</dt>
<dd>the mixing probabilities,
 an object of class <code>"numeric"</code></dd>

 <dt><code>order</code>:</dt>
<dd>Object of class <code>"numeric"</code> ~~</dd>

 <dt><code>shift</code>:</dt>
<dd>Object of class <code>"matrix"</code> ~~</dd>

 <dt><code>vcov</code>:</dt>
<dd>Object of class <code>"array"</code> ~~</dd>

 <dt><code>arcoef</code>:</dt>
<dd>Object of class <code>"raggedCoefV"</code> ~~</dd>

 
</dl>

<dl>
 <dt>fit_mixVAR</dt>
<dd><code>signature(x = "ANY", model = "MixAR")</code>: ...</dd>

 
</dl>

MixVAR-class: Class `"MixVAR"` --- mixture vector autoregressive models

Description

Arguments

Objects from the Class

Slots

Methods

Author

See Also