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	<title>The AstroStat Slog &#187; Peter Freeman</title>
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		<title>All your bias are belong to us</title>
		<link>http://groundtruth.info/AstroStat/slog/2007/astroph-07054199/</link>
		<comments>http://groundtruth.info/AstroStat/slog/2007/astroph-07054199/#comments</comments>
		<pubDate>Mon, 04 Jun 2007 21:42:38 +0000</pubDate>
		<dc:creator>vlk</dc:creator>
				<category><![CDATA[Bad AstroStat]]></category>
		<category><![CDATA[Fitting]]></category>
		<category><![CDATA[Methods]]></category>
		<category><![CDATA[Spectral]]></category>
		<category><![CDATA[Stat]]></category>
		<category><![CDATA[arXiv]]></category>
		<category><![CDATA[bias]]></category>
		<category><![CDATA[C-stat]]></category>
		<category><![CDATA[chi-square]]></category>
		<category><![CDATA[chisq]]></category>
		<category><![CDATA[Cstat]]></category>
		<category><![CDATA[parameter estimation]]></category>
		<category><![CDATA[Peter Freeman]]></category>
		<category><![CDATA[spectra]]></category>

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		<description><![CDATA[Leccardi &#38; Molendi (2007)  have a paper in A&#38;A (astro-ph/0705.4199) discussing the biases in parameter estimation when spectral fitting is confronted with  low counts data.  Not surprisingly, they find that the bias is higher for lower counts, for standard chisq compared to C-stat, for grouped data compared to ungrouped.  Peter Freeman [...]]]></description>
			<content:encoded><![CDATA[<p><a href="http://arxiv.org/abs/0705.4199" title="astro-ph/0705.4199">Leccardi &amp; Molendi (2007)</a>  have a paper in A&amp;A (<a href="http://arxiv.org/abs/0705.4199" title="astro-ph/0705.4199">astro-ph/0705.4199</a>) discussing the biases in parameter estimation when spectral fitting is confronted with  low counts data.  Not surprisingly, they find that the bias is higher for lower counts, for standard chisq compared to C-stat, for grouped data compared to ungrouped.  Peter Freeman talked about something like this at the 2003 X-ray Astronomy School at Wallops Island (<a href="http://xrayschool.gsfc.nasa.gov/docs/xrayschool-2003/freemanI.pdf" title="Statistics I slides">pdf1</a>, <a href="http://xrayschool.gsfc.nasa.gov/docs/xrayschool-2003/freemanII.pdf" title="Statistics II slides">pdf2</a>), and no doubt part of the problem also has to do with the <a href="http://groundtruth.info/AstroStat/slog/2007/on-the-unreliability-of-fitting/" title="fitting is an art">(un)reliability of the fitting process</a> when the chisq surface gets complicated.</p>
<p>Anyway, they propose an empirical method to reduce the bias by computing the probability distribution functions (<em>pdf</em>s) for various simulations, and then <em>averaging the pdfs</em> in groups of 3.  Seems to work, for reasons that escape me completely.</p>
<p>[<strong>Update:</strong> links to Peter's slides corrected]</p>
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