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    <title>topic Cluster and Outlier for temperature + depth in Spatial Statistics Questions</title>
    <link>https://community.esri.com/t5/spatial-statistics-questions/cluster-and-outlier-for-temperature-depth/m-p/49205#M168</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;SPAN&gt;I need to determine which temperature measurements are outliers at their depth.&amp;nbsp; Anselin Local Moran's I accounts for 2D autocorrelation, but how do I account for both variables?&lt;/SPAN&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Fri, 05 Apr 2013 16:23:52 GMT</pubDate>
    <dc:creator>PeterKasianchuk</dc:creator>
    <dc:date>2013-04-05T16:23:52Z</dc:date>
    <item>
      <title>Cluster and Outlier for temperature + depth</title>
      <link>https://community.esri.com/t5/spatial-statistics-questions/cluster-and-outlier-for-temperature-depth/m-p/49205#M168</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;SPAN&gt;I need to determine which temperature measurements are outliers at their depth.&amp;nbsp; Anselin Local Moran's I accounts for 2D autocorrelation, but how do I account for both variables?&lt;/SPAN&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 05 Apr 2013 16:23:52 GMT</pubDate>
      <guid>https://community.esri.com/t5/spatial-statistics-questions/cluster-and-outlier-for-temperature-depth/m-p/49205#M168</guid>
      <dc:creator>PeterKasianchuk</dc:creator>
      <dc:date>2013-04-05T16:23:52Z</dc:date>
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    <item>
      <title>Re: Cluster and Outlier for temperature + depth</title>
      <link>https://community.esri.com/t5/spatial-statistics-questions/cluster-and-outlier-for-temperature-depth/m-p/49206#M169</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;A href="https://geodacenter.asu.edu/ogeoda"&gt;GeoDa&lt;/A&gt;&lt;SPAN&gt; has a bivariate LISA available. &lt;/SPAN&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;SPAN&gt;Be sure that your interpretation of a bivatiate LISA is correct. The bivariate LISA is the crossproduct of the standardized values of one variable at location &lt;/SPAN&gt;&lt;SPAN style="font-style:italic;"&gt;i&lt;/SPAN&gt;&lt;SPAN&gt; (temperature) with those of the average neighboring values of the second variable (depth). You are testing whether localized correlations between values at location &lt;/SPAN&gt;&lt;SPAN style="font-style:italic;"&gt;i&lt;/SPAN&gt;&lt;SPAN&gt; and those of its neighbors are significantly different from what you would observe under spatial randomness. This would mean that a lo-hi outlier indicates that standardized temperature are significantly correlated with standardized depth.&lt;/SPAN&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Fri, 05 Apr 2013 20:48:53 GMT</pubDate>
      <guid>https://community.esri.com/t5/spatial-statistics-questions/cluster-and-outlier-for-temperature-depth/m-p/49206#M169</guid>
      <dc:creator>JeffreyEvans</dc:creator>
      <dc:date>2013-04-05T20:48:53Z</dc:date>
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