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    <title>topic Re: Jacknife analysis in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59508#M32639</link>
    <description>&lt;P&gt;What platform are you working in?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;There are some platforms that have Leave-one-out as an option for cross-validation.&amp;nbsp; However, if you don't see it as an option you can select K-fold cross-validation and set the K value to the number of rows you have in your data table.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Wed, 06 Jun 2018 20:27:41 GMT</pubDate>
    <dc:creator>Bill_Worley</dc:creator>
    <dc:date>2018-06-06T20:27:41Z</dc:date>
    <item>
      <title>Jacknife analysis</title>
      <link>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59496#M32634</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;I am interested to do Jacknife analysis (Leave - One - Out) to get an an estimate of error in the mean of a sample distribution. I saw Bootstrap in JMP Pro and appreciate if anyone has done Jacknife analysis in JMP.&amp;nbsp; Thanks.&lt;/P&gt;</description>
      <pubDate>Wed, 06 Jun 2018 18:53:19 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59496#M32634</guid>
      <dc:creator>AT</dc:creator>
      <dc:date>2018-06-06T18:53:19Z</dc:date>
    </item>
    <item>
      <title>Re: Jacknife analysis</title>
      <link>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59508#M32639</link>
      <description>&lt;P&gt;What platform are you working in?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;There are some platforms that have Leave-one-out as an option for cross-validation.&amp;nbsp; However, if you don't see it as an option you can select K-fold cross-validation and set the K value to the number of rows you have in your data table.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Wed, 06 Jun 2018 20:27:41 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59508#M32639</guid>
      <dc:creator>Bill_Worley</dc:creator>
      <dc:date>2018-06-06T20:27:41Z</dc:date>
    </item>
    <item>
      <title>Re: Jacknife analysis</title>
      <link>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59512#M32642</link>
      <description>&lt;P&gt;Jackknife is a bit different from bootstrap, as I'm sure you know, but there is some jackknife distance stuff for outlier analysis in the multivariate platform.&amp;nbsp; That's the only place I know of with any built-in jackknife analysis.&lt;/P&gt;&lt;P&gt;&lt;A href="https://www.jmp.com/support/help/14/distance-measures.shtml#240680" target="_self"&gt;https://www.jmp.com/support/help/14/distance-measures.shtml#240680&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;For your use case, you would probably need to script it up by hand.&amp;nbsp; It wouldn't be hard, although, why not bootstrap if you have access to JMP Pro.&amp;nbsp;&amp;nbsp;I thought of a way to vectorize the operation for a standard arithmetic mean.&amp;nbsp; Here's an example.&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-jsl"&gt;//Create Example Table
n = 100; //number of observations
dt = New Table("Jackknife Example",&amp;lt;&amp;lt; New Column("X",Formula(Random Normal(100,10))));
dt &amp;lt;&amp;lt; Add Rows(n);

//Jackknife Calculations
b = Identity(n)*-1 + 1; //matrix of 1s with 0s on the diagonal
Xvals = dt:X &amp;lt;&amp;lt; Get Values; //get column X as vector
repX = shape(Xvals, n, n); //repeat vector X n times in new matrix (repeated as row vectors)

means_jack = repX:*b*j(n,1,1)/(n-1); //compute jackknife means

//Results
xbar = mean(means_jack);
var_jack = (n-1)^2/n*stddev(means_jack)^2;
se_jack = sqrt(var_jack);&lt;/CODE&gt;&lt;/PRE&gt;</description>
      <pubDate>Wed, 06 Jun 2018 20:48:41 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59512#M32642</guid>
      <dc:creator>cwillden</dc:creator>
      <dc:date>2018-06-06T20:48:41Z</dc:date>
    </item>
    <item>
      <title>Re: Jacknife analysis</title>
      <link>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59700#M32680</link>
      <description>&lt;P&gt;Thanks for your suggestions. I have JMP PRO 14.&lt;/P&gt;</description>
      <pubDate>Thu, 07 Jun 2018 20:24:08 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59700#M32680</guid>
      <dc:creator>AT</dc:creator>
      <dc:date>2018-06-07T20:24:08Z</dc:date>
    </item>
    <item>
      <title>Re: Jacknife analysis</title>
      <link>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59702#M32682</link>
      <description>&lt;P&gt;Thanks Cameron for your help and script. I do have JMP Pro 14 and certainly can use Bootstrap as well.&lt;/P&gt;</description>
      <pubDate>Thu, 07 Jun 2018 20:41:08 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Jacknife-analysis/m-p/59702#M32682</guid>
      <dc:creator>AT</dc:creator>
      <dc:date>2018-06-07T20:41:08Z</dc:date>
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