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    <title>topic Re: Setting a Y intercept for a proc reg in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Setting-a-Y-intercept-for-a-proc-reg/m-p/117994#M6180</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt; I would like to hear what is the mean of revenue. My thoughts are that if it is far from 10000 than it can make sense.&lt;/P&gt;&lt;P&gt;Basically the R^2 is a measure which tells you how much more of variance of your variable REVENUE can be explained by your model compared to the model with intercept only.&lt;/P&gt;&lt;P&gt;I would say the R^2 in excel will be estimated using the model revenue=intercept + resid for comparison (which is estimated by average of revenue),&lt;/P&gt;&lt;P&gt;on the other hand the SAS will use model revenue=10000+resid for comparison and since this one could be pretty weak than the valu 99% additional fit can make sense.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Jakub&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Wed, 24 Apr 2013 07:34:00 GMT</pubDate>
    <dc:creator>chrej5am</dc:creator>
    <dc:date>2013-04-24T07:34:00Z</dc:date>
    <item>
      <title>Setting a Y intercept for a proc reg</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Setting-a-Y-intercept-for-a-proc-reg/m-p/117993#M6179</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;In excel, I have used a second-order polynomial forecast which is fit to intercept the Y axis at 10,000. Excel reports an R^2 of 0.25 for this relationship.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I'm trying to replicate this in SAS in order to observe significance levels/standard errors with the following model:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;proc reg data=data2;&lt;/P&gt;&lt;P&gt;model revenue=xr xr2 /white spec;&lt;/P&gt;&lt;P&gt;restrict intercept=10000;&lt;/P&gt;&lt;P&gt;run;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;This model outputs parameter intercepts identical to Excel's. Unfortunately, the R^2 is insane at 0.9963.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;SAS results report: "Restrictions on intercept. R-Square is redefined". How should I be interpreting the R^2 then? Also, is there any way to output a graphical output which exhibits the confidence bands off the base of the data?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Wed, 24 Apr 2013 03:42:16 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Setting-a-Y-intercept-for-a-proc-reg/m-p/117993#M6179</guid>
      <dc:creator>Wolfram</dc:creator>
      <dc:date>2013-04-24T03:42:16Z</dc:date>
    </item>
    <item>
      <title>Re: Setting a Y intercept for a proc reg</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Setting-a-Y-intercept-for-a-proc-reg/m-p/117994#M6180</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt; I would like to hear what is the mean of revenue. My thoughts are that if it is far from 10000 than it can make sense.&lt;/P&gt;&lt;P&gt;Basically the R^2 is a measure which tells you how much more of variance of your variable REVENUE can be explained by your model compared to the model with intercept only.&lt;/P&gt;&lt;P&gt;I would say the R^2 in excel will be estimated using the model revenue=intercept + resid for comparison (which is estimated by average of revenue),&lt;/P&gt;&lt;P&gt;on the other hand the SAS will use model revenue=10000+resid for comparison and since this one could be pretty weak than the valu 99% additional fit can make sense.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Jakub&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Wed, 24 Apr 2013 07:34:00 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Setting-a-Y-intercept-for-a-proc-reg/m-p/117994#M6180</guid>
      <dc:creator>chrej5am</dc:creator>
      <dc:date>2013-04-24T07:34:00Z</dc:date>
    </item>
    <item>
      <title>Re: Setting a Y intercept for a proc reg</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Setting-a-Y-intercept-for-a-proc-reg/m-p/117995#M6181</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;If it were me, I would subtract 10,000 from my Y variable and use the NOINT option on the model statement to consider lines that pass through the origin. (But then I'd ask myself, "why am I considering only no-intercept models.)&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Wed, 24 Apr 2013 12:45:32 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Setting-a-Y-intercept-for-a-proc-reg/m-p/117995#M6181</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2013-04-24T12:45:32Z</dc:date>
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