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 *
 * This help file was generated from aryule.sci using help_from_sci().
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          xmlns="http://docbook.org/ns/docbook"
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  <refnamediv>
    <refname>aryule</refname>
    <refpurpose>Fit an AR (p)-model with Yule-Walker estimates.</refpurpose>
  </refnamediv>


<refsynopsisdiv>
   <title>Syntax</title>
   <synopsis>
   a = aryule(x, p)
   [a, v] = aryule(x, p)
   [a, v, k] = aryule(x, p)
   
   </synopsis>
</refsynopsisdiv>

<refsection>
   <title>Parameters</title>
   <variablelist>
        <varlistentry>
            <term>x:</term>
            <listitem><para> Vector of real or complex numbers, length &gt; 2.</para></listitem>
        </varlistentry>
        <varlistentry>
            <term>p:</term>
            <listitem><para> Positive integer value &lt; length(x) - 1.</para></listitem>
        </varlistentry>
        <varlistentry>
            <term>a:</term>
            <listitem><para> AR coefficients.</para></listitem>
        </varlistentry>
        <varlistentry>
            <term>v:</term>
            <listitem><para> Variance of the white noise.</para></listitem>
        </varlistentry>
        <varlistentry>
            <term>k:</term>
            <listitem><para> Reflection coefficients to be used in the lattice filter.</para></listitem>
        </varlistentry>
   </variablelist>
</refsection>

<refsection>
   <title>Description</title>
   <para>
This function fits an AR (p)-model with Yule-Walker estimates. The first argument is the data vector to be estimated.
   </para>
   <para>
</para>
</refsection>

<refsection>
   <title>Examples</title>
   <programlisting role="example"><![CDATA[
aryule([1, 2, 3, 4, 5], 2)

   ]]></programlisting>
</refsection>
</refentry>
