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    <title>topic Re: Help on Constraint Linear Regression in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178744#M9274</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thank you very much!&lt;/P&gt;&lt;P&gt;I will try that.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Mon, 14 Apr 2014 19:53:05 GMT</pubDate>
    <dc:creator>FelixHugh</dc:creator>
    <dc:date>2014-04-14T19:53:05Z</dc:date>
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      <title>Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178733#M9263</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi, I wanted to set a constraint on a linear regression model (y = b0+b1*x1+b2*x2+e), such that the the predicted value (b0+b1*x1+b2*x2) is positive. Is there a SAS procedure that can be used for the purpose. Any help is greatly appreciated!&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 10:54:41 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178733#M9263</guid>
      <dc:creator>FelixHugh</dc:creator>
      <dc:date>2014-04-14T10:54:41Z</dc:date>
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    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178734#M9264</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Easy way: Fit log(y) and back transform.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;More difficult way: Use PROC MODEL with a RESTRICT statement.&amp;nbsp; I know it can be done, but I have never tried it myself.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Steve Denham&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 13:08:11 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178734#M9264</guid>
      <dc:creator>SteveDenham</dc:creator>
      <dc:date>2014-04-14T13:08:11Z</dc:date>
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    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178735#M9265</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thank you Steve for your suggestions!&lt;/P&gt;&lt;P&gt;I did try PROC MODEL. I found it difficult to set up a RESTRICT statement for the purpose of bounding all the predicted values of y as positive.&lt;/P&gt;&lt;P&gt;I tried to use log(y) as the dependent variable, but the parameter estimates are not close to the values from the paper, which I was trying to replicate.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 14:05:17 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178735#M9265</guid>
      <dc:creator>FelixHugh</dc:creator>
      <dc:date>2014-04-14T14:05:17Z</dc:date>
    </item>
    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178736#M9266</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;As stated, your problem is impossible unless b1=b2=0 and b0&amp;gt;0.&amp;nbsp; Otherwise there will always be a value of (x1, x2) for which the predicted value will be negative.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;If you know that (x1,x2) are restricted to some domain (like the unit square), then it is possible.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 14:06:34 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178736#M9266</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2014-04-14T14:06:34Z</dc:date>
    </item>
    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178737#M9267</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Doc Steve,&lt;/P&gt;&lt;P&gt;If I want all the coefficient ( b0 b1 b2)&amp;nbsp; greater than zero. what I am going to do ?&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Best.&lt;/P&gt;&lt;P&gt;Xia Keshan&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 14:15:38 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178737#M9267</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2014-04-14T14:15:38Z</dc:date>
    </item>
    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178738#M9268</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thank you Rick for your reply!&lt;/P&gt;&lt;P&gt;The dependent variable is variance in stock market returns, which is why I want to make sure the predicted variance is positive.&lt;/P&gt;&lt;P&gt;The independent variables include variance and market return from last period. Market return can be negative.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 14:17:44 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178738#M9268</guid>
      <dc:creator>FelixHugh</dc:creator>
      <dc:date>2014-04-14T14:17:44Z</dc:date>
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    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178739#M9269</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Doc Rick.&lt;/P&gt;&lt;P&gt;What about survival analysis ? in Survival Analysis , dependent variable(survival time) is always&amp;nbsp; &amp;gt; 0.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 14:19:11 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178739#M9269</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2014-04-14T14:19:11Z</dc:date>
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    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178740#M9270</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Hi, sorry to just jump in. I think you may try to set multiple RESTRICT statements (restrict b0&amp;gt;0, b1&amp;gt;0, b2&amp;gt;0).&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 14:21:07 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178740#M9270</guid>
      <dc:creator>FelixHugh</dc:creator>
      <dc:date>2014-04-14T14:21:07Z</dc:date>
    </item>
    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178741#M9271</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;In survival analysis, logistic regression, Poisson regression, and other models, the linear portion of the model is transformed by a "link function" to ensure that the result is positive.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 15:01:10 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178741#M9271</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2014-04-14T15:01:10Z</dc:date>
    </item>
    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178742#M9272</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;The RESTRICT statement in PROC REG only handles equality constraints, but you can use the BOUNDS statement in PROC NLIN to restrict the range of the parameters.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 15:07:29 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178742#M9272</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2014-04-14T15:07:29Z</dc:date>
    </item>
    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178743#M9273</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Because your response variable is a variance, I recommend that you model it as a gamma distribution, with a log link. That is, use GENMOD or GLIMMIX, and choose dist=gamma and link=log. The gamma often works very well as an approximation for the true distribution of a variance at small (finite) sample sizes. You can still get predictions for the original scale in an output file. For instance,&lt;/P&gt;&lt;P&gt;proc glimmix ;&lt;/P&gt;&lt;P&gt;model var = .... / dist=gamma link=log s ;&lt;/P&gt;&lt;P&gt;output out=pred pred(blup ilink)=predicted;&lt;/P&gt;&lt;P&gt;run;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;There are many other options for the output file.&lt;/P&gt;&lt;P&gt;Schabenberger and Pierce (2002 textbook) give an example of a regression analysis of a variance dependent variable using this idea (but with GENMOD).&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 19:14:48 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178743#M9273</guid>
      <dc:creator>lvm</dc:creator>
      <dc:date>2014-04-14T19:14:48Z</dc:date>
    </item>
    <item>
      <title>Re: Help on Constraint Linear Regression</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178744#M9274</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;Thank you very much!&lt;/P&gt;&lt;P&gt;I will try that.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 14 Apr 2014 19:53:05 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Help-on-Constraint-Linear-Regression/m-p/178744#M9274</guid>
      <dc:creator>FelixHugh</dc:creator>
      <dc:date>2014-04-14T19:53:05Z</dc:date>
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