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Data Analysis and Statistics for Geography, Environmental Science, and Engineering
book

Data Analysis and Statistics for Geography, Environmental Science, and Engineering

by Miguel F. Acevedo
December 2012
Beginner content levelBeginner
557 pages
19h 5m
English
CRC Press
Content preview from Data Analysis and Statistics for Geography, Environmental Science, and Engineering
444 Data Analysis and Statistics for Geography, Environmental Science, and Engineering
> plot(xp, border = “grey”)
> plot(xd.nb, coords, add=T)
Next, we need weights for neighborhood structure. In this case, a simple calculation of weights is
the inverse of the distance; i.e., the closest the regions, the larger the weight (the closest two regions
are, the more intense the neighbor effect).
We can get distances between each pair
> xd.dists <- nbdists(xd.nb, coords)
> summary(unlist(xd.dists) )
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.008062 0.178700 0.286900 0.296100 0.434300 0.499700
>
And also we can get an intensity of neighborhood using the inv
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Publisher Resources

ISBN: 9781439885017