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	<title>Comments for Mike Love's blog</title>
	<atom:link href="http://mikelove.wordpress.com/comments/feed/" rel="self" type="application/rss+xml" />
	<link>http://mikelove.wordpress.com</link>
	<description></description>
	<lastBuildDate>Sun, 26 Aug 2012 18:01:35 +0000</lastBuildDate>
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		<title>Comment on SVG in R by Mathias Riechert</title>
		<link>http://mikelove.wordpress.com/2009/01/25/svg-in-r/#comment-8782</link>
		<dc:creator><![CDATA[Mathias Riechert]]></dc:creator>
		<pubDate>Sun, 26 Aug 2012 18:01:35 +0000</pubDate>
		<guid isPermaLink="false">http://mikelove.wordpress.com/?p=495#comment-8782</guid>
		<description><![CDATA[Hello,

same question here, I&#039;d like to render paths with devSVGTips (I&#039;m plotting a shape file), but cannot get it to work. Do you have any hints? 

Thanks alot,

Mathias]]></description>
		<content:encoded><![CDATA[<p>Hello,</p>
<p>same question here, I&#8217;d like to render paths with devSVGTips (I&#8217;m plotting a shape file), but cannot get it to work. Do you have any hints? </p>
<p>Thanks alot,</p>
<p>Mathias</p>
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	</item>
	<item>
		<title>Comment on Bootstrap-t confidence intervals by mikelove</title>
		<link>http://mikelove.wordpress.com/2010/02/15/bootstrap-t/#comment-8773</link>
		<dc:creator><![CDATA[mikelove]]></dc:creator>
		<pubDate>Wed, 08 Aug 2012 09:31:10 +0000</pubDate>
		<guid isPermaLink="false">http://mikelove.wordpress.com/?p=683#comment-8773</guid>
		<description><![CDATA[Hi Aida, 

see here: http://en.wikipedia.org/wiki/Pivotal_quantity

it&#039;s like a z-score, in that we want to scale the differences down by the sample standard deviation and then rescale afterward.]]></description>
		<content:encoded><![CDATA[<p>Hi Aida, </p>
<p>see here: <a href="http://en.wikipedia.org/wiki/Pivotal_quantity" rel="nofollow">http://en.wikipedia.org/wiki/Pivotal_quantity</a></p>
<p>it&#8217;s like a z-score, in that we want to scale the differences down by the sample standard deviation and then rescale afterward.</p>
]]></content:encoded>
	</item>
	<item>
		<title>Comment on Bootstrap-t confidence intervals by Masa Aida</title>
		<link>http://mikelove.wordpress.com/2010/02/15/bootstrap-t/#comment-8772</link>
		<dc:creator><![CDATA[Masa Aida]]></dc:creator>
		<pubDate>Sun, 05 Aug 2012 01:14:25 +0000</pubDate>
		<guid isPermaLink="false">http://mikelove.wordpress.com/?p=683#comment-8772</guid>
		<description><![CDATA[Good article, question below -- you are using, SD -- but it should be SE?

se.x = sd(x) / sqrt(len(n))

rather than ?

sd.x = sd(x)]]></description>
		<content:encoded><![CDATA[<p>Good article, question below &#8212; you are using, SD &#8212; but it should be SE?</p>
<p>se.x = sd(x) / sqrt(len(n))</p>
<p>rather than ?</p>
<p>sd.x = sd(x)</p>
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	<item>
		<title>Comment on Statistics is more important than trigonometry by Charlotte2005</title>
		<link>http://mikelove.wordpress.com/2011/01/17/statistics-trigonometr/#comment-8764</link>
		<dc:creator><![CDATA[Charlotte2005]]></dc:creator>
		<pubDate>Thu, 07 Jun 2012 20:51:09 +0000</pubDate>
		<guid isPermaLink="false">http://mikelove.wordpress.com/?p=828#comment-8764</guid>
		<description><![CDATA[I sorta&#039; agree; with this caveat. Isn&#039;t a lot of statistics dependent upon what has been learned by the study of trig?]]></description>
		<content:encoded><![CDATA[<p>I sorta&#8217; agree; with this caveat. Isn&#8217;t a lot of statistics dependent upon what has been learned by the study of trig?</p>
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	<item>
		<title>Comment on Bootstrap-t confidence intervals by An Introduction to the Bootstrap : Summary &#171; Book Reviews</title>
		<link>http://mikelove.wordpress.com/2010/02/15/bootstrap-t/#comment-8763</link>
		<dc:creator><![CDATA[An Introduction to the Bootstrap : Summary &#171; Book Reviews]]></dc:creator>
		<pubDate>Sun, 27 May 2012 14:35:29 +0000</pubDate>
		<guid isPermaLink="false">http://mikelove.wordpress.com/?p=683#comment-8763</guid>
		<description><![CDATA[[...] Implicitly , the second method based on bootstrap percentiles knows the right transformation so that the resultant data is normal. I did not understand this part until I wrote some code in R. The code clearly showed that percentile methods work better than normal based methods and using percentile methods does not mean that we should know the transformation function. Couple of nice features of percentile based methods are 1) it is range preserving and 2) it is transformation respecting. For all those people who dread remembering formulae for confidence intervals, this chapter is a big relief as bootstrapping gives you good estimates of the parameter’s cut off points for a given alpha. Although one must not mistake this method to be like nirvana as it does not correct the bias your estimator. I worked out an exercise problem of this chapter and found that out of the normal based interval, percentile based interval and t-based interval that was introduced in chapter 12, the t-based interval to have a better coverage probability than the other two estimators. Also came across a blog post that seems to be agreeing to what I say here. [...]]]></description>
		<content:encoded><![CDATA[<p>[...] Implicitly , the second method based on bootstrap percentiles knows the right transformation so that the resultant data is normal. I did not understand this part until I wrote some code in R. The code clearly showed that percentile methods work better than normal based methods and using percentile methods does not mean that we should know the transformation function. Couple of nice features of percentile based methods are 1) it is range preserving and 2) it is transformation respecting. For all those people who dread remembering formulae for confidence intervals, this chapter is a big relief as bootstrapping gives you good estimates of the parameter’s cut off points for a given alpha. Although one must not mistake this method to be like nirvana as it does not correct the bias your estimator. I worked out an exercise problem of this chapter and found that out of the normal based interval, percentile based interval and t-based interval that was introduced in chapter 12, the t-based interval to have a better coverage probability than the other two estimators. Also came across a blog post that seems to be agreeing to what I say here. [...]</p>
]]></content:encoded>
	</item>
	<item>
		<title>Comment on Last.fm user distribution, long tail of mainstream-ness by Leveraging the Long Tail &#124; digital rainforest</title>
		<link>http://mikelove.wordpress.com/2007/06/12/lastfm-user-distribution-long-tail-of-mainstream-ness/#comment-8748</link>
		<dc:creator><![CDATA[Leveraging the Long Tail &#124; digital rainforest]]></dc:creator>
		<pubDate>Sat, 05 May 2012 11:10:02 +0000</pubDate>
		<guid isPermaLink="false">http://mikelove.wordpress.com/2007/06/12/lastfm-user-distribution-long-tail-of-mainstream-ness/#comment-8748</guid>
		<description><![CDATA[[...] Last.fm Wikipedia - Last.fm Anatomy of the Long Tail: Ordinary People with Extraordinary Tastes Last.fm user distribution, long tail of mainstream-ness Last.fm: The Long Tail music picker Music Recommendation and the Long Tail Last.fm the Robotic DJ [...]]]></description>
		<content:encoded><![CDATA[<p>[...] Last.fm Wikipedia - Last.fm Anatomy of the Long Tail: Ordinary People with Extraordinary Tastes Last.fm user distribution, long tail of mainstream-ness Last.fm: The Long Tail music picker Music Recommendation and the Long Tail Last.fm the Robotic DJ [...]</p>
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		<title>Comment on New Yorker debases English language with insane umlaut convention by Umlaut? Diaeresis? What? &#171; write it good</title>
		<link>http://mikelove.wordpress.com/2007/08/27/new-yorker-debases-english-language-with-insane-umlaut-convention/#comment-8742</link>
		<dc:creator><![CDATA[Umlaut? Diaeresis? What? &#171; write it good]]></dc:creator>
		<pubDate>Fri, 27 Apr 2012 02:03:53 +0000</pubDate>
		<guid isPermaLink="false">http://mikelove.wordpress.com/2007/08/27/new-yorker-debases-english-language-with-insane-umlaut-convention/#comment-8742</guid>
		<description><![CDATA[[...] a few confused blog posts about the habit (see here, or here), the New Yorker have finally addressed it and its usage with this delightful article. While [...]]]></description>
		<content:encoded><![CDATA[<p>[...] a few confused blog posts about the habit (see here, or here), the New Yorker have finally addressed it and its usage with this delightful article. While [...]</p>
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