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    <title>MATLAB Central Newsreader - Log-likelihood</title>
    <description>Feed for thread: Log-likelihood</description>
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      <pubDate>Thu, 16 Oct 2008 14:32:01 -0400</pubDate>
      <title>Log-likelihood</title>
      <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/237660#605700</link>
      <author>thiago silva</author>
      <description>Hi,&lt;br&gt;
&lt;br&gt;
I am using dfittool to plot my data as well to plot some distributions. I would like to choose the distribution that best fit to my data. Can I use the log-likelihood to decide which distribution is the best? How can I compare them using log-likelihood? the one closest to zero is the best?&lt;br&gt;
&lt;br&gt;
Thanks in advance,&lt;br&gt;
&lt;br&gt;
Thiago</description>
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    <item>
      <pubDate>Thu, 16 Oct 2008 14:59:37 -0400</pubDate>
      <title>Re: Log-likelihood</title>
      <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/237660#605711</link>
      <author>Ting</author>
      <description>Thiago,&lt;br&gt;
&amp;nbsp;&amp;nbsp;People usually use maximum likelihood method to estimate parameters &lt;br&gt;
for   a chosen model, but You should not use log-likelihood to compare &lt;br&gt;
different models. Because, generally a model with more parameters tends &lt;br&gt;
to have larger likelihood.&lt;br&gt;
&lt;br&gt;
There is no simple answer for how to decide the goodness of fit for &lt;br&gt;
distribution fit. For details, please see my reply for your question on &lt;br&gt;
&quot;Doing Goodness of Fit test in dfittool'.&lt;br&gt;
&lt;br&gt;
-Ting Su&lt;br&gt;
Mathworks.</description>
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