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    <title>topic Re: Proc Robustreg in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Robustreg/m-p/72834#M3505</link>
    <description>ROBUSTREG wasn't designed for this situation.&lt;BR /&gt;
&lt;BR /&gt;
A possible way around this would be to fit the model with the known coefficient, and then compute residuals and do ROBUSTREG on the residuals. I haven't thought this through 100% to convince myself that is reasonable, but it sounds like it would work at first glance.</description>
    <pubDate>Wed, 31 Mar 2010 19:45:15 GMT</pubDate>
    <dc:creator>Paige</dc:creator>
    <dc:date>2010-03-31T19:45:15Z</dc:date>
    <item>
      <title>Proc Robustreg</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Robustreg/m-p/72833#M3504</link>
      <description>Hello and great forum!!&lt;BR /&gt;
&lt;BR /&gt;
I have undertaken a fixed income portfolio analysis for one of my University's endowment funds, and I am working on a model to calculate returns. I have constructed a multiple linear equation and know one of the regressor coefficients. Does anyone know of a way for me to hold the known value constant, while letting sas adjust the coefficients on the other independent variables?&lt;BR /&gt;
&lt;BR /&gt;
Any help or direction is greatly appreciated!&lt;BR /&gt;
&lt;BR /&gt;
Tim</description>
      <pubDate>Wed, 31 Mar 2010 16:25:01 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Robustreg/m-p/72833#M3504</guid>
      <dc:creator>deleted_user</dc:creator>
      <dc:date>2010-03-31T16:25:01Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Robustreg</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Robustreg/m-p/72834#M3505</link>
      <description>ROBUSTREG wasn't designed for this situation.&lt;BR /&gt;
&lt;BR /&gt;
A possible way around this would be to fit the model with the known coefficient, and then compute residuals and do ROBUSTREG on the residuals. I haven't thought this through 100% to convince myself that is reasonable, but it sounds like it would work at first glance.</description>
      <pubDate>Wed, 31 Mar 2010 19:45:15 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Robustreg/m-p/72834#M3505</guid>
      <dc:creator>Paige</dc:creator>
      <dc:date>2010-03-31T19:45:15Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Robustreg</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Robustreg/m-p/72835#M3506</link>
      <description>If you have the model&lt;BR /&gt;
&lt;BR /&gt;
&amp;nbsp;&amp;nbsp;Y = b0 + b1*X1 + b2*X2 + ... + bk*Xk + C*Z&lt;BR /&gt;
&lt;BR /&gt;
where C is known a priori, then you can rewrite the equation as:&lt;BR /&gt;
&lt;BR /&gt;
&amp;nbsp;&amp;nbsp;Y* = Y - C*Z = b0 + b1*X1 + b2*X2 + ... + bk*Xk&lt;BR /&gt;
&lt;BR /&gt;
So, all you need to do is to construct a new response variable in which you subtract the known effect from the original response.  You can then fit your model employing this new response and predictors X1, X2, ..., Xk.</description>
      <pubDate>Thu, 01 Apr 2010 19:15:06 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Robustreg/m-p/72835#M3506</guid>
      <dc:creator>Dale</dc:creator>
      <dc:date>2010-04-01T19:15:06Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Robustreg</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Robustreg/m-p/72836#M3507</link>
      <description>Thank you, Paige and Dale!&lt;BR /&gt;
&lt;BR /&gt;
My data now looks great!&lt;BR /&gt;
&lt;BR /&gt;
Tim</description>
      <pubDate>Fri, 02 Apr 2010 04:37:26 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Robustreg/m-p/72836#M3507</guid>
      <dc:creator>deleted_user</dc:creator>
      <dc:date>2010-04-02T04:37:26Z</dc:date>
    </item>
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