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    <title>Recent replies to "Log-likelihood ratio and information theory"</title>
    <description>Recent replies to "Log-likelihood ratio and information theory"</description>
    <link>http://network.nature.com/forums/statistics/404</link>
    <language>en-us</language>
    <ttl>40</ttl>
    <item>
      <title>Reply from Bob O'Hara</title>
      <description>&lt;p&gt;No replies yet?  :-)&lt;/p&gt;


	&lt;p&gt;David Anderson has a &lt;a href="http://www.amazon.co.uk/Model-Based-Inference-Life-Sciences/dp/0387740732/ref=sr_1_2?ie=UTF8&amp;#38;s=books&amp;#38;qid=1203576150&amp;#38;sr=1-2"&gt;new book out&lt;/a&gt; which, I&amp;#8217;m sure, discusses information theory and likelihood.  K-L divergence is the basis of a host of information criteria that we use to compare models.&lt;/p&gt;


	&lt;p&gt;Alternatively, you could take the Bayesian route, and have a look at &lt;a href="http://bayes.wustl.edu/"&gt;Jaynes&amp;#8217; work&lt;/a&gt;, which is closely related to entropy methods.&lt;/p&gt;


	&lt;p&gt;Bob&lt;/p&gt;</description>
      <pubDate>Thu, 21 Feb 2008 06:45:55 -0000</pubDate>
      <link>http://network.nature.com/forums/statistics/404?page=1#reply-2784</link>
      <dc:creator>Bob O'Hara</dc:creator>
      <guid>http://network.nature.com/forums/statistics/404?page=1#reply-2784</guid>
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