I have large data sets on regular grids which I wish to analyse
geostatistically, so I have been using two-dimensional Fourier transforms
to obtain the autocorrelation functions, which I then subtract from the
variances to obtain the semivariograms.
I am happy with the results, but I am unsure as to how to fit a model. I
would like to use weighted least squares, but I have not been able to
locate a formula for the variance of each lag of a spectrally determined
autocorrelation function, which I would need to do the weighting. Does
anyone know such a formula? Have people successfully fit semivariograms
estimated in this way using other methods?
University of British Columbia
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