[GIS] R geographically weighted regression GWModel

rregression

I am exploring the use of GWmodel to run some GWR regressions. I set it up and tried to run some sample regressions using the gwr.basic function, but ran into the following error,

Error in t(X * W.i) : dims [product 4659] do not match the length of object [0]

This is what I did,

gwr.basic(Y~X+I(X^2), data = spdf,bw = bw.gwr.1, kernel = "gausssian", adaptive = TRUE, F123.test = TRUE)

And here is the summary of my input data set, spdf

**summary(spdf)
    Object of class SpatialPointsDataFrame
    Coordinates:
              min       max
    Long 95.71586 103.70657
    Lat  40.12491  42.89963
    Is projected: NA 
    proj4string : [NA]
    Number of points: 1553
    Data attributes:
         Y             X    
     Min.   : 51.33   Min.   :100  
     1st Qu.:196.19   1st Qu.:115  
     Median :224.74   Median :123  
     Mean   :216.66   Mean   :123  
     3rd Qu.:245.70   3rd Qu.:131  
     Max.   :346.72   Max.   :150**

What may be happening?

Best Answer

I believe that you need to set the argument "longlat=TRUE". Since your data is in geographic coordinates it is likely that the kernel is being incorrectly defined. You also may want to explicitly specify the data slot "data = spdf@data".

Please use caution with specification of the GWR method in anything other than exploratory analysis of nonstationarity. It is a somewhat suspect method and there are a number of papers that indicate the incorrectness of this method in both type I & II error and severe bias in coefficients. That said, it can be a great exploratory tool, just not an inferential one.

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