This piece shows how to use the Spatial Data Analysis-Add-In (Version 0.92) for JMP to calculate the most commonly used metrics to measure spatial autocorrelation: Moran's I and Geary's Ratio.
2015-05-04
Exploring Spatial Autocorrelation: Moran's I and Geary's Ratio
While using autocorrelation statistics for time series data is quite common, one has to dig a bit deeper to evaluate spatial autocorrelation for some given data. Spatial autocorrelation might be a starting-point for any analysis of spatial data to get a first impression if places that are close to each other are similar in regards of a variable of interest.
This piece shows how to use the Spatial Data Analysis-Add-In (Version 0.92) for JMP to calculate the most commonly used metrics to measure spatial autocorrelation: Moran's I and Geary's Ratio.
This piece shows how to use the Spatial Data Analysis-Add-In (Version 0.92) for JMP to calculate the most commonly used metrics to measure spatial autocorrelation: Moran's I and Geary's Ratio.
Labels:
JMP,
Spatial Statistics
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