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    <title>rpy2 rpy r python kriging gstat on fritzvd</title>
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    <lastBuildDate>Mon, 26 Nov 2012 13:48:56 +0000</lastBuildDate><atom:link href="https://fritzvd.com/blog/tags/rpy2-rpy-r-python-kriging-gstat/index.xml" rel="self" type="application/rss+xml" />
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      <title>Kriging in R in Python</title>
      <link>https://fritzvd.com/blog/2012/11/26/kriging-in-r-in-python/</link>
      <pubDate>Mon, 26 Nov 2012 13:48:56 +0000</pubDate>
      
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      <description>This might be a repost of some sort. However I found that it was kind of hard to find anything about this specific topic. So here it goes.
Kriging is a geostatistical method to be able translate point data to a grid, to find out where you can predict stuff really well and where the variance is really high. As always GIGO (garbage in garbage out). But it is at least a large improvement from interpolation techniques such as Inversed Distance Weighting (IDW) which is often implemented in GIS software.</description>
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