<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>D.M. Heisey</dc:creator>
  <dc:date>2012</dc:date>
  <dc:description>One can joke that 'exciting statistics' is an oxymoron, but it is neither a joke nor an exaggeration to say that these are exciting times to be involved in statistical ecology. As Halstead &lt;i&gt;et al.&lt;/i&gt;'s (2012) paper nicely exemplifies, recently developed Bayesian analyses can now be used to extract insights from data using techniques that would have been unavailable to the ecological researcher just a decade ago. Some object to this, implying that the subjective priors of the Bayesian approach is the pathway to perdition (e.g. Lele &amp; Dennis, 2009). It is reasonable to ask whether these new approaches are really giving us anything that we could not obtain with traditional tried-and-true frequentist approaches. I believe the answer is a clear yes.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1111/j.1469-1795.2012.00532.x</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>The Zoological Society of London</dc:publisher>
  <dc:title>Bayesian shared frailty models for regional inference about wildlife survival</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>