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    <title>topic compare many distributions in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/compare-many-distributions/m-p/41415#M1770</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I have over 100 distributions (Auto dealerships) and I need to use a time series to forecast each dealership's sale for the next 12 months with monthly data I have for the past 10 years.&amp;nbsp; I want to develop a time series model, but first I want to &lt;SPAN style="text-decoration: underline;"&gt;compare&lt;/SPAN&gt; dealerships to see if any have the dependent variable (which in this case is the prices) in common (perhaps Proc corr, I don't know) and see if I can group some so that I don't have to model 100 stores, but instead model only on say 60 or 50, or whatever the results show.. I can say 4 stores show similar trends and cycles, seasonality and increase/decrease in price, that I can group Sore 1/2/3/4 together..&lt;/P&gt;&lt;P&gt;How can this be done?&amp;nbsp; Is proc corr the right tool or perhaps a proc glm ??&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Thu, 03 Nov 2011 20:05:22 GMT</pubDate>
    <dc:creator>podarum</dc:creator>
    <dc:date>2011-11-03T20:05:22Z</dc:date>
    <item>
      <title>compare many distributions</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/compare-many-distributions/m-p/41415#M1770</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I have over 100 distributions (Auto dealerships) and I need to use a time series to forecast each dealership's sale for the next 12 months with monthly data I have for the past 10 years.&amp;nbsp; I want to develop a time series model, but first I want to &lt;SPAN style="text-decoration: underline;"&gt;compare&lt;/SPAN&gt; dealerships to see if any have the dependent variable (which in this case is the prices) in common (perhaps Proc corr, I don't know) and see if I can group some so that I don't have to model 100 stores, but instead model only on say 60 or 50, or whatever the results show.. I can say 4 stores show similar trends and cycles, seasonality and increase/decrease in price, that I can group Sore 1/2/3/4 together..&lt;/P&gt;&lt;P&gt;How can this be done?&amp;nbsp; Is proc corr the right tool or perhaps a proc glm ??&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 03 Nov 2011 20:05:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/compare-many-distributions/m-p/41415#M1770</guid>
      <dc:creator>podarum</dc:creator>
      <dc:date>2011-11-03T20:05:22Z</dc:date>
    </item>
    <item>
      <title>compare many distributions</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/compare-many-distributions/m-p/41416#M1771</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;It will be interesting to see what our statisticians have to recommend.&amp;nbsp; I would have thought a discrimant function or factor analysis, or possibly a decision tree or neural net.&amp;nbsp; However, I am definitely not well versed in time series and don't know if there are similar types of analyses that also take time into account.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 03 Nov 2011 20:15:56 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/compare-many-distributions/m-p/41416#M1771</guid>
      <dc:creator>art297</dc:creator>
      <dc:date>2011-11-03T20:15:56Z</dc:date>
    </item>
    <item>
      <title>compare many distributions</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/compare-many-distributions/m-p/41417#M1772</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;See also &lt;A _jive_internal="true" href="https://communities.sas.com/message/39698#39698"&gt;http://communities.sas.com/message/39698#39698&lt;/A&gt; for the perspective of Time Series analysts.&lt;/P&gt;&lt;P&gt;I have seen some people use PROC VARCLUS to group similar variables into clusters of variables with similar behavior. They then model a representative variable from each cluster, or construct the "average" of each cluster and model that.&amp;nbsp; &lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 03 Nov 2011 22:11:26 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/compare-many-distributions/m-p/41417#M1772</guid>
      <dc:creator>Rick_SAS</dc:creator>
      <dc:date>2011-11-03T22:11:26Z</dc:date>
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