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    <title>topic Re: How to output 200K parameters in PROC MCMC? in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-output-200K-parameters-in-PROC-MCMC/m-p/527575#M26674</link>
    <description>&lt;P&gt;Hi,&lt;/P&gt;
&lt;P&gt;An easy way is to assume the posterior on each effect is Gaussian:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;1) Monitor the posterior distributions of the random effects.&lt;/P&gt;
&lt;P&gt;2) Write ODS output postsumint=Px;&lt;/P&gt;
&lt;P&gt;3) In a subsequent datastep, sample from the mean and Standard deviation given in Px (or just use the posterior info in Px.)&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Let me know if this isn't what you are thinking...&lt;/P&gt;
&lt;P&gt;G&lt;/P&gt;</description>
    <pubDate>Wed, 16 Jan 2019 00:26:46 GMT</pubDate>
    <dc:creator>Garnett</dc:creator>
    <dc:date>2019-01-16T00:26:46Z</dc:date>
    <item>
      <title>How to output 200K parameters in PROC MCMC?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-output-200K-parameters-in-PROC-MCMC/m-p/524129#M26567</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I want to use PROC MCMC to run a random-effects linear negative binomial (NB1) model and estimate ~200,000 random intercepts (as an alternative to NLMIXED).&amp;nbsp; Since the OUTPOST= dataset can only save up to 32,767 variables, what approaches can I take to be able to output the posterior samples for all of the ~200K random-effects parameters?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks,&lt;/P&gt;&lt;P&gt;Andrea&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;P.S. I have SAS v9.4 (TS1M4) and SAS/STAT 14.2.&lt;/P&gt;</description>
      <pubDate>Wed, 02 Jan 2019 17:12:14 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-output-200K-parameters-in-PROC-MCMC/m-p/524129#M26567</guid>
      <dc:creator>AndreaB_</dc:creator>
      <dc:date>2019-01-02T17:12:14Z</dc:date>
    </item>
    <item>
      <title>Re: How to output 200K parameters in PROC MCMC?</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/How-to-output-200K-parameters-in-PROC-MCMC/m-p/527575#M26674</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;
&lt;P&gt;An easy way is to assume the posterior on each effect is Gaussian:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;1) Monitor the posterior distributions of the random effects.&lt;/P&gt;
&lt;P&gt;2) Write ODS output postsumint=Px;&lt;/P&gt;
&lt;P&gt;3) In a subsequent datastep, sample from the mean and Standard deviation given in Px (or just use the posterior info in Px.)&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Let me know if this isn't what you are thinking...&lt;/P&gt;
&lt;P&gt;G&lt;/P&gt;</description>
      <pubDate>Wed, 16 Jan 2019 00:26:46 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/How-to-output-200K-parameters-in-PROC-MCMC/m-p/527575#M26674</guid>
      <dc:creator>Garnett</dc:creator>
      <dc:date>2019-01-16T00:26:46Z</dc:date>
    </item>
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