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    <title>topic Re: How to predict the value for a location using other predictor variables? in Spatial Statistics Questions</title>
    <link>https://community.esri.com/t5/spatial-statistics-questions/how-to-predict-the-value-for-a-location-using/m-p/124833#M437</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;SPAN&gt;Given the problem that you stated I do not know what you mean by "spatial relationships". It sounds like a simple OLS or GWR (both available in ArcGIS) would work. If for some reason these approaches will not work consider imputation. For an imputation analysis you will need to use a statistical software. R has very nice capacity to read/write GIS data and very mature imputation approaches (and is free). Take a look at this thread. &lt;/SPAN&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;A href="http://forums.arcgis.com/threads/25949-cluster-analysis-based-on-multiple-variables?highlight=imputation"&gt;http://forums.arcgis.com/threads/25949-cluster-analysis-based-on-multiple-variables?highlight=imputation&lt;/A&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Thu, 26 May 2011 16:37:47 GMT</pubDate>
    <dc:creator>JeffreyEvans</dc:creator>
    <dc:date>2011-05-26T16:37:47Z</dc:date>
    <item>
      <title>How to predict the value for a location using other predictor variables?</title>
      <link>https://community.esri.com/t5/spatial-statistics-questions/how-to-predict-the-value-for-a-location-using/m-p/124832#M436</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;SPAN&gt;Hi all&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;I have a point shapefile that has 3 variables like precipitation, temperature, and the runoff. I am using precipitation and temperature as predictor variables and runoff as dependent variable. Using the spatial relation of these variables, I need to predict runoff for the points in a shapefile for any changes in temperature and precipitation as shown below. &lt;/SPAN&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;SPAN&gt;Eg &lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;ID PPT TEMP RUNOFF&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;1 110 25 40&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;2 100 18 34&lt;/SPAN&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;SPAN&gt;ID PPT TEMP RUNOFF&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;1 150 24 ?&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;2 90 17 ?&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt; &lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;I think this problem is different then interpolation because I am not interested in predicting for unknown locations as well as I have multiple variables to be taken care of. I am just wondering if I can perfom any test like this in ArcGIS? If so, which tool should I use? Any light on this area would be highly appreciated?&lt;/SPAN&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;SPAN&gt;Thanks!&lt;/SPAN&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 24 May 2011 04:04:30 GMT</pubDate>
      <guid>https://community.esri.com/t5/spatial-statistics-questions/how-to-predict-the-value-for-a-location-using/m-p/124832#M436</guid>
      <dc:creator>fabefabe</dc:creator>
      <dc:date>2011-05-24T04:04:30Z</dc:date>
    </item>
    <item>
      <title>Re: How to predict the value for a location using other predictor variables?</title>
      <link>https://community.esri.com/t5/spatial-statistics-questions/how-to-predict-the-value-for-a-location-using/m-p/124833#M437</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;SPAN&gt;Given the problem that you stated I do not know what you mean by "spatial relationships". It sounds like a simple OLS or GWR (both available in ArcGIS) would work. If for some reason these approaches will not work consider imputation. For an imputation analysis you will need to use a statistical software. R has very nice capacity to read/write GIS data and very mature imputation approaches (and is free). Take a look at this thread. &lt;/SPAN&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;A href="http://forums.arcgis.com/threads/25949-cluster-analysis-based-on-multiple-variables?highlight=imputation"&gt;http://forums.arcgis.com/threads/25949-cluster-analysis-based-on-multiple-variables?highlight=imputation&lt;/A&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Thu, 26 May 2011 16:37:47 GMT</pubDate>
      <guid>https://community.esri.com/t5/spatial-statistics-questions/how-to-predict-the-value-for-a-location-using/m-p/124833#M437</guid>
      <dc:creator>JeffreyEvans</dc:creator>
      <dc:date>2011-05-26T16:37:47Z</dc:date>
    </item>
    <item>
      <title>Re: How to predict the value for a location using other predictor variables?</title>
      <link>https://community.esri.com/t5/spatial-statistics-questions/how-to-predict-the-value-for-a-location-using/m-p/124834#M438</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;SPAN&gt;Hi Kami, &lt;/SPAN&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;SPAN&gt;Examining the relationships between the variables that you have in your data can be done using Ordinary Least Squares regression and Geographically Weighted Regression, both available in ArcGIS.&amp;nbsp; To get started using OLS and GWR, you may want to check out the &lt;/SPAN&gt;&lt;A href="http://training.esri.com/acb2000/showdetl.cfm?DID=6&amp;amp;Product_ID=942"&gt;Regression Analysis Basics&lt;/A&gt;&lt;SPAN&gt; seminar, which is free from the Virtual Campus website.&lt;/SPAN&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;SPAN&gt;You may also want to check out the other resources available for spatial statistics here:&amp;nbsp; &lt;/SPAN&gt;&lt;A href="http://esriurl.com/spatialstats"&gt;http://esriurl.com/spatialstats&lt;/A&gt;&lt;SPAN&gt;.&lt;/SPAN&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;SPAN&gt;Hope this helps.&lt;/SPAN&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;SPAN&gt;Lauren Rosenshein&lt;/SPAN&gt;&lt;BR /&gt;&lt;SPAN&gt;Geoprocessing Product Engineer&lt;/SPAN&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 14 Jun 2011 17:39:52 GMT</pubDate>
      <guid>https://community.esri.com/t5/spatial-statistics-questions/how-to-predict-the-value-for-a-location-using/m-p/124834#M438</guid>
      <dc:creator>LaurenRosenshein</dc:creator>
      <dc:date>2011-06-14T17:39:52Z</dc:date>
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