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    <title>topic Re: univariate and correlated distribution in SAS/IML Software and Matrix Computations</title>
    <link>https://communities.sas.com/t5/SAS-IML-Software-and-Matrix/univariate-and-correlated-distribution/m-p/153714#M1406</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Can you say more? The title of your post says "univariate and correlated," but your message says "two bivariates," so I am confused. Are you trying to generate X from a multivariate normal and then generate a binary response based on the X variables? Such as simulated data from a logistic model?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;You can use the RANDNORMAL function to generate correlated normal data. For example:&lt;/P&gt;&lt;P&gt;proc iml;&lt;/P&gt;&lt;P&gt;call randseed(1);&lt;/P&gt;&lt;P&gt;N = 5000;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* sample size */&lt;/P&gt;&lt;P&gt;Mean = {1 2};&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* mean of population */&lt;/P&gt;&lt;P&gt;Cov = {2.4 3, 3 8.1};/* covariance of population */&lt;/P&gt;&lt;P&gt;x = RandNormal( N, Mean, Cov );&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Mon, 12 May 2014 13:04:22 GMT</pubDate>
    <dc:creator>Rick_SAS</dc:creator>
    <dc:date>2014-05-12T13:04:22Z</dc:date>
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      <title>univariate and correlated distribution</title>
      <link>https://communities.sas.com/t5/SAS-IML-Software-and-Matrix/univariate-and-correlated-distribution/m-p/153713#M1405</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;Could anyone explain me how to generate two bivariates and correlated normal distributions with 5000&amp;nbsp; sample size?&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 12 May 2014 01:34:12 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-IML-Software-and-Matrix/univariate-and-correlated-distribution/m-p/153713#M1405</guid>
      <dc:creator>dustychair</dc:creator>
      <dc:date>2014-05-12T01:34:12Z</dc:date>
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    <item>
      <title>Re: univariate and correlated distribution</title>
      <link>https://communities.sas.com/t5/SAS-IML-Software-and-Matrix/univariate-and-correlated-distribution/m-p/153714#M1406</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Can you say more? The title of your post says "univariate and correlated," but your message says "two bivariates," so I am confused. Are you trying to generate X from a multivariate normal and then generate a binary response based on the X variables? Such as simulated data from a logistic model?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;You can use the RANDNORMAL function to generate correlated normal data. For example:&lt;/P&gt;&lt;P&gt;proc iml;&lt;/P&gt;&lt;P&gt;call randseed(1);&lt;/P&gt;&lt;P&gt;N = 5000;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* sample size */&lt;/P&gt;&lt;P&gt;Mean = {1 2};&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; /* mean of population */&lt;/P&gt;&lt;P&gt;Cov = {2.4 3, 3 8.1};/* covariance of population */&lt;/P&gt;&lt;P&gt;x = RandNormal( N, Mean, Cov );&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 12 May 2014 13:04:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-IML-Software-and-Matrix/univariate-and-correlated-distribution/m-p/153714#M1406</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2014-05-12T13:04:22Z</dc:date>
    </item>
    <item>
      <title>Re: univariate and correlated distribution</title>
      <link>https://communities.sas.com/t5/SAS-IML-Software-and-Matrix/univariate-and-correlated-distribution/m-p/153715#M1407</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I am sorry, but I do not understand.&amp;nbsp; The RMSE of WHAT goes down?&amp;nbsp; As you know, you can generate binary variables as 0/1 or as 1/0.&amp;nbsp; What do you observe if you let p --&amp;gt; 1-p?&amp;nbsp; In your program, that would correspond to &lt;/P&gt;&lt;P&gt;z[i,j] = (p&amp;lt;=u);&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 13 May 2014 17:37:03 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-IML-Software-and-Matrix/univariate-and-correlated-distribution/m-p/153715#M1407</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2014-05-13T17:37:03Z</dc:date>
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