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	<title>Comments for Erik Barry Erhardt, PhD</title>
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	<link>http://statacumen.com</link>
	<description>"I bring excellence to everything I do."</description>
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		<title>Comment on Paper published: Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study by Erik Barry Erhardt, PhD &#187; A simulation toolbox for fMRI data: SimTB</title>
		<link>http://statacumen.com/2011/10/14/paper-published-capturing-inter-subject-variability-with-group-independent-component-analysis-of-fmri-data-a-simulation-study/comment-page-1/#comment-11694</link>
		<dc:creator>Erik Barry Erhardt, PhD &#187; A simulation toolbox for fMRI data: SimTB</dc:creator>
		<pubDate>Sat, 10 Dec 2011 02:56:05 +0000</pubDate>
		<guid isPermaLink="false">http://statacumen.com/?p=869#comment-11694</guid>
		<description>[...] Update: both papers have been published, simulation toolbox and inter-subject variability. [...]</description>
		<content:encoded><![CDATA[<p>[...] Update: both papers have been published, simulation toolbox and inter-subject variability. [...]</p>
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		<title>Comment on Paper published: SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability by Erik Barry Erhardt, PhD &#187; A simulation toolbox for fMRI data: SimTB</title>
		<link>http://statacumen.com/2011/12/09/paper-published-simtb-a-simulation-toolbox-for-fmri-data/comment-page-1/#comment-11693</link>
		<dc:creator>Erik Barry Erhardt, PhD &#187; A simulation toolbox for fMRI data: SimTB</dc:creator>
		<pubDate>Sat, 10 Dec 2011 02:52:11 +0000</pubDate>
		<guid isPermaLink="false">http://statacumen.com/?p=955#comment-11693</guid>
		<description>[...] Allen and I recently submitted two papers that detail a simulation toolbox for fMRI data (SimTB) and capturing inter-subject variability with group independent component [...]</description>
		<content:encoded><![CDATA[<p>[...] Allen and I recently submitted two papers that detail a simulation toolbox for fMRI data (SimTB) and capturing inter-subject variability with group independent component [...]</p>
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	<item>
		<title>Comment on A simulation toolbox for fMRI data: SimTB by Erik Barry Erhardt, PhD &#187; Paper published: SimTB, a simulation toolbox for fMRI data</title>
		<link>http://statacumen.com/2011/05/11/a-simulation-toolbox-for-fmri-data-simtb/comment-page-1/#comment-11692</link>
		<dc:creator>Erik Barry Erhardt, PhD &#187; Paper published: SimTB, a simulation toolbox for fMRI data</dc:creator>
		<pubDate>Sat, 10 Dec 2011 02:49:39 +0000</pubDate>
		<guid isPermaLink="false">http://statacumen.com/?p=714#comment-11692</guid>
		<description>[...] paper detailing our simulation toolbox (SimTB) has been published in [...]</description>
		<content:encoded><![CDATA[<p>[...] paper detailing our simulation toolbox (SimTB) has been published in [...]</p>
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		<title>Comment on A simulation toolbox for fMRI data: SimTB by Erik Barry Erhardt, PhD &#187; Paper published: Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study</title>
		<link>http://statacumen.com/2011/05/11/a-simulation-toolbox-for-fmri-data-simtb/comment-page-1/#comment-10833</link>
		<dc:creator>Erik Barry Erhardt, PhD &#187; Paper published: Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study</dc:creator>
		<pubDate>Fri, 14 Oct 2011 23:03:36 +0000</pubDate>
		<guid isPermaLink="false">http://statacumen.com/?p=714#comment-10833</guid>
		<description>[...] paper using our simulation toolbox (SimTB) detailing what can be learned about multi-subject ICA on fMRI data has been published in [...]</description>
		<content:encoded><![CDATA[<p>[...] paper using our simulation toolbox (SimTB) detailing what can be learned about multi-subject ICA on fMRI data has been published in [...]</p>
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	<item>
		<title>Comment on Eri-Eri-Eri-Erik, the fastest, smoothest, dreamiest swinger by Erik Barry Erhardt, PhD &#187; Mary Wesley, CDSS youth intern 2011-2012</title>
		<link>http://statacumen.com/2011/08/26/eri-eri-eri-erik-the-fastest-smoothest-dreamiest-swinger/comment-page-1/#comment-10437</link>
		<dc:creator>Erik Barry Erhardt, PhD &#187; Mary Wesley, CDSS youth intern 2011-2012</dc:creator>
		<pubDate>Wed, 07 Sep 2011 23:54:49 +0000</pubDate>
		<guid isPermaLink="false">http://statacumen.com/?p=797#comment-10437</guid>
		<description>[...] (2009-11) who I&#8217;ve learned from at workshops around the country, and has appeared in another post. Here&#8217;s Mary&#8217;s introduction as intern from the CDSS website: Dear friends: I am [...]</description>
		<content:encoded><![CDATA[<p>[...] (2009-11) who I&#8217;ve learned from at workshops around the country, and has appeared in another post. Here&#8217;s Mary&#8217;s introduction as intern from the CDSS website: Dear friends: I am [...]</p>
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	<item>
		<title>Comment on Penalized-x, new pool solitaire game by x</title>
		<link>http://statacumen.com/2008/12/29/penalized-x-new-pool-solitaire-game/comment-page-1/#comment-9696</link>
		<dc:creator>x</dc:creator>
		<pubDate>Wed, 29 Jun 2011 16:27:35 +0000</pubDate>
		<guid isPermaLink="false">http://statacumen.com/?p=184#comment-9696</guid>
		<description>There should be an additional penalty for scratching, e.g., an additional ball or two is pulled out.</description>
		<content:encoded><![CDATA[<p>There should be an additional penalty for scratching, e.g., an additional ball or two is pulled out.</p>
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		<title>Comment on Richard Wilson: All join hands, thirty years of community dance by Erik Barry Erhardt, PhD &#187; Youth dancing, spring 2011</title>
		<link>http://statacumen.com/2011/03/20/richard-wilson-all-join-hands/comment-page-1/#comment-8733</link>
		<dc:creator>Erik Barry Erhardt, PhD &#187; Youth dancing, spring 2011</dc:creator>
		<pubDate>Mon, 21 Mar 2011 02:26:54 +0000</pubDate>
		<guid isPermaLink="false">http://statacumen.com/?p=686#comment-8733</guid>
		<description>[...] Wilson, of Wilson family fame, led a song to end the night.  She had learned the song that day and brought her guitar, which [...]</description>
		<content:encoded><![CDATA[<p>[...] Wilson, of Wilson family fame, led a song to end the night.  She had learned the song that day and brought her guitar, which [...]</p>
]]></content:encoded>
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	<item>
		<title>Comment on Visions by Erik Barry Erhardt, PhD &#187; Youth dancing, spring 2011</title>
		<link>http://statacumen.com/2010/03/15/visions/comment-page-1/#comment-8732</link>
		<dc:creator>Erik Barry Erhardt, PhD &#187; Youth dancing, spring 2011</dc:creator>
		<pubDate>Mon, 21 Mar 2011 02:22:47 +0000</pubDate>
		<guid isPermaLink="false">http://statacumen.com/?p=520#comment-8732</guid>
		<description>[...] happy to write about two touching events consistent with my vision that I helped organize the last few months: teaching middle schoolers folk dance, and organizing a [...]</description>
		<content:encoded><![CDATA[<p>[...] happy to write about two touching events consistent with my vision that I helped organize the last few months: teaching middle schoolers folk dance, and organizing a [...]</p>
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		<title>Comment on Wishart distribution in WinBUGS, nonstandard parameterization by Bob Carlton</title>
		<link>http://statacumen.com/2009/07/02/wishart-distribution-in-winbugs-nonstandard-parameterization/comment-page-1/#comment-8361</link>
		<dc:creator>Bob Carlton</dc:creator>
		<pubDate>Thu, 24 Feb 2011 17:51:39 +0000</pubDate>
		<guid isPermaLink="false">http://statacumen.com/?p=361#comment-8361</guid>
		<description>I was also puzzled at first about the camel example -&gt; but reached a different conclusion. The problem with the camel example is that the degree of freedom parameter (v) of the wishart is not &gt;= dim(matrix)+2, therefore this prior is not an integrateable density. This means that E(v,matrix) is not interpretable in the usual way. One can easily see this if you just draw from the wishart in winbugs setting the degree of freedom parameter to 4 (not using it as a prior, just drawing from the distribution), then everything behaves as expected. Stating this in a more convenient Inverse Wishart as a conjugate to a normal way:
You want E=Inv-Wishart(v,V) with both E and V in Covariance Form
then prec.E=Bugs-Wishart(v,V)  and  v&gt;=dim(V)+2 and V=covariance matrix
results in prec.E equals the precision matrix for the normal and Inverse[prec.E] is the covariance matrix. The camel example can violates this because  v not &gt;= dim(V)+2, so it is not a good example for the general interpretation and general cases.
mean	sd	MC_error	val2.5pc	median	val97.5pc	start	sample
	T[1,1]	0.001262	0.028	3.075E-4	1.053E-4	4.268E-4	0.004854	1001	8400
	T[1,2]	-7.499E-5	0.006116	6.748E-5	-0.001702	3.507E-6	0.001648	1001	8400
	T[2,1]	-7.499E-5	0.006116	6.748E-5	-0.001702	3.507E-6	0.001648	1001	8400
	T[2,2]	0.001042	0.007392	7.701E-5	1.081E-4	4.236E-4	0.004577	1001	8400
	prec.T[1,1]	3981.0	2849.0	37.23	473.9	3320.0	11350.0	1001	8400
	prec.T[1,2]	-15.8	1970.0	20.64	-4085.0	-36.18	4077.0	1001	8400
	prec.T[2,1]	-15.8	1970.0	20.64	-4085.0	-36.18	4077.0	1001	8400
	prec.T[2,2]	3973.0	2810.0	26.06	517.2	3324.0	11130.0	1001	8400</description>
		<content:encoded><![CDATA[<p>I was also puzzled at first about the camel example -&gt; but reached a different conclusion. The problem with the camel example is that the degree of freedom parameter (v) of the wishart is not &gt;= dim(matrix)+2, therefore this prior is not an integrateable density. This means that E(v,matrix) is not interpretable in the usual way. One can easily see this if you just draw from the wishart in winbugs setting the degree of freedom parameter to 4 (not using it as a prior, just drawing from the distribution), then everything behaves as expected. Stating this in a more convenient Inverse Wishart as a conjugate to a normal way:<br />
You want E=Inv-Wishart(v,V) with both E and V in Covariance Form<br />
then prec.E=Bugs-Wishart(v,V)  and  v&gt;=dim(V)+2 and V=covariance matrix<br />
results in prec.E equals the precision matrix for the normal and Inverse[prec.E] is the covariance matrix. The camel example can violates this because  v not &gt;= dim(V)+2, so it is not a good example for the general interpretation and general cases.<br />
mean	sd	MC_error	val2.5pc	median	val97.5pc	start	sample<br />
	T[1,1]	0.001262	0.028	3.075E-4	1.053E-4	4.268E-4	0.004854	1001	8400<br />
	T[1,2]	-7.499E-5	0.006116	6.748E-5	-0.001702	3.507E-6	0.001648	1001	8400<br />
	T[2,1]	-7.499E-5	0.006116	6.748E-5	-0.001702	3.507E-6	0.001648	1001	8400<br />
	T[2,2]	0.001042	0.007392	7.701E-5	1.081E-4	4.236E-4	0.004577	1001	8400<br />
	prec.T[1,1]	3981.0	2849.0	37.23	473.9	3320.0	11350.0	1001	8400<br />
	prec.T[1,2]	-15.8	1970.0	20.64	-4085.0	-36.18	4077.0	1001	8400<br />
	prec.T[2,1]	-15.8	1970.0	20.64	-4085.0	-36.18	4077.0	1001	8400<br />
	prec.T[2,2]	3973.0	2810.0	26.06	517.2	3324.0	11130.0	1001	8400</p>
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		<title>Comment on Dance by Erik Barry Erhardt, PhD &#187; Contra dance: Sashay, Sassy Kat</title>
		<link>http://statacumen.com/dance/comment-page-1/#comment-8084</link>
		<dc:creator>Erik Barry Erhardt, PhD &#187; Contra dance: Sashay, Sassy Kat</dc:creator>
		<pubDate>Fri, 04 Feb 2011 17:37:46 +0000</pubDate>
		<guid isPermaLink="false">http://statacumen.com/?page_id=492#comment-8084</guid>
		<description>[...] Dance [...]</description>
		<content:encoded><![CDATA[<p>[...] Dance [...]</p>
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