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I apply Thiessen Polygons interpolation using the krige command in the gstat R package. Using krige without a variogram model sets automatically krige function to perform IDW, and when nmax parameter is set to 1, it is actually performing thiessen polygons interpolation. What I have is this:

dec_vor = krige(Dec ~ 1, st, grd, nmax = 1)

Then, when I want to perform cross validation, i do this:

dec_vor_cv = krige.cv(Dec ~ 1, st, nfold = 52, dec_vor)

and I get this error message:

"Error in load.variogram.model(object$model[[name]], c(i - 1, i - 1)) : 
  model should be of mode variogramModel (use function vgm)"
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  • (perhaps better known as 'nearest neighbor' interpolation)
    – Robert Hijmans
    Commented Jun 25, 2015 at 3:12

1 Answer 1

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Although this may not be directly apparent from the documentation, the third (unnamed) argument to your krige.cv call is assumed to be a variogram model, and is absorbed by the argument model. Since dec_vor is the outcome of a call to krige, it is not, hence the error message.

It is not clear to me why you would pass dec_vor to krige.cv, as krige.cv loops over the observations in st only, nothing else.

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  • thank you for your response! When I do not pass dec_vor to krige.cv, the command works fine. The reason why I wanted to to pass dec_vor to krige.cv is because I wanted krige.cv to evaluate dev_vor. Is this wrong?
    – Maria Karypidou
    Commented Jun 25, 2015 at 8:08
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    then you should replace st with dev_vor; this will however depending on the density of grd nearly certainly give perfect results that have nothing to do with how good interpolation of st went.
    – Edzer Pebesma
    Commented Jun 25, 2015 at 12:39

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