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    <title>topic Re: AIC for self created nonlinear model in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/AIC-for-self-created-nonlinear-model/m-p/86340#M38489</link>
    <description>&lt;P&gt;You can calculate the AICc for the continuous response using this formula:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="AICc.png" style="width: 999px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/14916i62F2157AF35A4C2F/image-size/large?v=v2&amp;amp;px=999" role="button" title="AICc.png" alt="AICc.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Where n = sample size, p = number of model parameters, and SSE for the fitted model. The log() is the natural logarithm function.&lt;/P&gt;</description>
    <pubDate>Fri, 21 Dec 2018 12:26:11 GMT</pubDate>
    <dc:creator>Mark_Bailey</dc:creator>
    <dc:date>2018-12-21T12:26:11Z</dc:date>
    <item>
      <title>AIC for self created nonlinear model</title>
      <link>https://community.jmp.com/t5/Discussions/AIC-for-self-created-nonlinear-model/m-p/86335#M38485</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;How can I get AIC values for a self created nonlinear model (by column formula)?&lt;/P&gt;&lt;P&gt;I choose Analyse &amp;gt; Specialized modeling &amp;gt; Nonlinear , I put my formula column as X, the response column as Y, I get convergence. But how can I get AIC values to compare the model with a linear model? Or are there other ways to compare my formula model with a linear one?&lt;/P&gt;&lt;P&gt;Thanks in advance for your help!&lt;/P&gt;</description>
      <pubDate>Fri, 21 Dec 2018 09:34:58 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/AIC-for-self-created-nonlinear-model/m-p/86335#M38485</guid>
      <dc:creator>frietje</dc:creator>
      <dc:date>2018-12-21T09:34:58Z</dc:date>
    </item>
    <item>
      <title>Re: AIC for self created nonlinear model</title>
      <link>https://community.jmp.com/t5/Discussions/AIC-for-self-created-nonlinear-model/m-p/86340#M38489</link>
      <description>&lt;P&gt;You can calculate the AICc for the continuous response using this formula:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="AICc.png" style="width: 999px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/14916i62F2157AF35A4C2F/image-size/large?v=v2&amp;amp;px=999" role="button" title="AICc.png" alt="AICc.png" /&gt;&lt;/span&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Where n = sample size, p = number of model parameters, and SSE for the fitted model. The log() is the natural logarithm function.&lt;/P&gt;</description>
      <pubDate>Fri, 21 Dec 2018 12:26:11 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/AIC-for-self-created-nonlinear-model/m-p/86340#M38489</guid>
      <dc:creator>Mark_Bailey</dc:creator>
      <dc:date>2018-12-21T12:26:11Z</dc:date>
    </item>
    <item>
      <title>Re: AIC for self created nonlinear model</title>
      <link>https://community.jmp.com/t5/Discussions/AIC-for-self-created-nonlinear-model/m-p/86341#M38490</link>
      <description>Thanks!</description>
      <pubDate>Fri, 21 Dec 2018 12:44:03 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/AIC-for-self-created-nonlinear-model/m-p/86341#M38490</guid>
      <dc:creator>frietje</dc:creator>
      <dc:date>2018-12-21T12:44:03Z</dc:date>
    </item>
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