<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Expected value? IMSL? in Intel® oneAPI Math Kernel Library</title>
    <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Expected-value-IMSL/m-p/796671#M2714</link>
    <description>Hello, &lt;BR /&gt;&lt;BR /&gt;Not sure if MKL can help here. &lt;BR /&gt;MKL have VSL, which provide function for Random Number Generators, &lt;BR /&gt;for example, &lt;H1 class="topictitle1"&gt;&lt;SPAN class="sectionBodyText"&gt;vRngGaussian(), &lt;/SPAN&gt;&lt;SPAN class="sectionBodyText"&gt;Generates normally distributed random numbers.&lt;BR /&gt;and &lt;BR /&gt;&lt;BR /&gt;VSL Summary Statistics routines&lt;/SPAN&gt;&lt;SPAN class="sectionBodyText"&gt;compute basic statistical estimates for single and double precision multi-dimensional datasets. &lt;BR /&gt;for example, &lt;BR /&gt;variance-covariance/correlation matrix. &lt;BR /&gt;&lt;BR /&gt;anyway, you may refer the MKL reference manual at &lt;/SPAN&gt;&lt;A href="http://software.intel.com/en-us/articles/intel-math-kernel-library-documentation/" class="sectionBodyText"&gt;http://software.intel.com/en-us/articles/intel-math-kernel-library-documentation/&lt;/A&gt;&lt;SPAN class="sectionBodyText"&gt;. &lt;BR /&gt;&lt;BR /&gt;Regards,&lt;BR /&gt;Ying H.&lt;/SPAN&gt;&lt;/H1&gt;</description>
    <pubDate>Thu, 08 Mar 2012 08:07:51 GMT</pubDate>
    <dc:creator>Ying_H_Intel</dc:creator>
    <dc:date>2012-03-08T08:07:51Z</dc:date>
    <item>
      <title>Expected value? IMSL?</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Expected-value-IMSL/m-p/796669#M2712</link>
      <description>Hi&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;Let say I have a function in fortran that is F(X,e1,e2) where e1 e2 are distributedbivariate normal.&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;Can somebody point me to an example of how to calculate the expected value of F? If it makes it easier I can use IMSL.&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;Thanks for the help!&lt;/DIV&gt;</description>
      <pubDate>Mon, 05 Mar 2012 15:55:59 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Expected-value-IMSL/m-p/796669#M2712</guid>
      <dc:creator>ignacio82</dc:creator>
      <dc:date>2012-03-05T15:55:59Z</dc:date>
    </item>
    <item>
      <title>Expected value? IMSL?</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Expected-value-IMSL/m-p/796670#M2713</link>
      <description>I think a better forum for this would be out Math Kernel Library user forum. MKL is bundled with the compiler and perhaps they have a solution. &lt;BR /&gt;&lt;BR /&gt;I will transfer this issue to that forum&lt;BR /&gt;&lt;BR /&gt;ron</description>
      <pubDate>Thu, 08 Mar 2012 00:11:04 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Expected-value-IMSL/m-p/796670#M2713</guid>
      <dc:creator>Ron_Green</dc:creator>
      <dc:date>2012-03-08T00:11:04Z</dc:date>
    </item>
    <item>
      <title>Expected value? IMSL?</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Expected-value-IMSL/m-p/796671#M2714</link>
      <description>Hello, &lt;BR /&gt;&lt;BR /&gt;Not sure if MKL can help here. &lt;BR /&gt;MKL have VSL, which provide function for Random Number Generators, &lt;BR /&gt;for example, &lt;H1 class="topictitle1"&gt;&lt;SPAN class="sectionBodyText"&gt;vRngGaussian(), &lt;/SPAN&gt;&lt;SPAN class="sectionBodyText"&gt;Generates normally distributed random numbers.&lt;BR /&gt;and &lt;BR /&gt;&lt;BR /&gt;VSL Summary Statistics routines&lt;/SPAN&gt;&lt;SPAN class="sectionBodyText"&gt;compute basic statistical estimates for single and double precision multi-dimensional datasets. &lt;BR /&gt;for example, &lt;BR /&gt;variance-covariance/correlation matrix. &lt;BR /&gt;&lt;BR /&gt;anyway, you may refer the MKL reference manual at &lt;/SPAN&gt;&lt;A href="http://software.intel.com/en-us/articles/intel-math-kernel-library-documentation/" class="sectionBodyText"&gt;http://software.intel.com/en-us/articles/intel-math-kernel-library-documentation/&lt;/A&gt;&lt;SPAN class="sectionBodyText"&gt;. &lt;BR /&gt;&lt;BR /&gt;Regards,&lt;BR /&gt;Ying H.&lt;/SPAN&gt;&lt;/H1&gt;</description>
      <pubDate>Thu, 08 Mar 2012 08:07:51 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Expected-value-IMSL/m-p/796671#M2714</guid>
      <dc:creator>Ying_H_Intel</dc:creator>
      <dc:date>2012-03-08T08:07:51Z</dc:date>
    </item>
    <item>
      <title>Expected value? IMSL?</title>
      <link>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Expected-value-IMSL/m-p/796672#M2715</link>
      <description>Depending on whether e&lt;SUB&gt;1&lt;/SUB&gt; and e&lt;SUB&gt;2&lt;/SUB&gt; are independent, in which case there are four random variables, or are dependent, in which case there are two or three random variables, you have to evaluate a two, three or four dimensional integral over the random variables, with ranges from - to +. It may or may not be possible to perform some of the integrations analytically. &lt;BR /&gt;&lt;BR /&gt;The details will depend on the specific functional form of F. It is not clear if X is independent of the random variables. &lt;BR /&gt;&lt;BR /&gt;One of the earliest examples of such a calculation is to be found in calculating the temperature of a gas in terms of the root-mean-square velocity of the molecules (J.C. Maxwell's Kinetic Theory).&lt;BR /&gt;</description>
      <pubDate>Thu, 08 Mar 2012 16:15:52 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/Expected-value-IMSL/m-p/796672#M2715</guid>
      <dc:creator>mecej4</dc:creator>
      <dc:date>2012-03-08T16:15:52Z</dc:date>
    </item>
  </channel>
</rss>

