Conditional on the underlying beta random field, Cov(Zi, Zj |Y )=0. So then, the spatial
sill estimated from the sample proportions should be relatively unchanged from the beta sill,
35
%2
Y = V ar(Y ), with some estimation error of course. The additional variability from the
beta-binomial structure can then be thought of as the nugget term, ⌧ 2 = V ar 4 Z
n
5
!V ar(Y ).
For the spatial range, there should be no change throughout the transformation, since the
same sample locations are used at each point and the transformation from Gaussian to beta
is one-to-one. There may be some slight fluctuations in the estimated spatial range at the
binomial level due to sampling, but overall it should stay constant.
Then, the variogram parameters for the sample proportions, in terms of the beta shape
parameters, are
Conditional on the underlying beta random field, Cov(Zi, Zj |Y )=0. So then, the spatialsill estimated from the sample proportions should be relatively unchanged from the beta sill,35%2Y = V ar(Y ), with some estimation error of course. The additional variability from thebeta-binomial structure can then be thought of as the nugget term, ⌧ 2 = V ar 4 Zn5!V ar(Y ).For the spatial range, there should be no change throughout the transformation, since thesame sample locations are used at each point and the transformation from Gaussian to betais one-to-one. There may be some slight fluctuations in the estimated spatial range at thebinomial level due to sampling, but overall it should stay constant.Then, the variogram parameters for the sample proportions, in terms of the beta shapeparameters, are
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