mix_variance-methods

mix_variance,MixAR,missing,missing,missing-method

mix_variance,MixAR,missing,missing,numeric-method

mix_variance,MixAR,numeric,numeric,missing-method

Methods for <code>mix_variance</code> in package &#8220;pcts&#8221;

methods

internal

 MixAR 

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

mix_variance-methods function

<dl><dt><code>signature(model = "MixAR", x = "missing", index = "missing", xcond = "missing")</code></dt>
<dd></dd>
<dt><code>signature(model = "MixAR", x = "missing", index = "missing", xcond = "numeric")</code></dt>
<dd></dd>
<dt><code>signature(model = "MixAR", x = "numeric", index = "numeric", xcond = "missing")</code></dt>
<dd></dd>
</dl>

Methods

Methods for mix_variance — mix_variance-methods

<dl>

<dt><code>signature(model = "MixAR", x = "missing", index = "missing", xcond = "missing")</code></dt>
<dd></dd>


<dt><code>signature(model = "MixAR", x = "missing", index = "missing", xcond = "numeric")</code></dt>
<dd></dd>


<dt><code>signature(model = "MixAR", x = "numeric", index = "numeric", xcond = "missing")</code></dt>
<dd></dd>


</dl>

mix_variance-methods: Methods for mix_variance

Description

Arguments

Methods

See Also