R: GLS fitting of variogram parameters

fit.variogram.gls {gstat} | R Documentation

## GLS fitting of variogram parameters

### Description

Fits variogram parameters (nugget, sill, range) to variogram cloud, using GLS (generalized least squares) fitting. Only for direct variograms.

### Usage

    fit.variogram.gls(formula, data, model, maxiter = 30,
    		eps = .01, trace = TRUE, ignoreInitial = TRUE, cutoff = Inf,
    		plot = FALSE)

### Arguments

`formula` | formula defining the response vector and (possible) regressors; in case of absence of regressors, use e.g. `z~1`
`data` | object of class Spatial
`model` | variogram model to be fitted, output of `vgm`
`maxiter` | maximum number of iterations
`eps` | convergence criterium
`trace` | logical; if TRUE, prints parameter trace
`ignoreInitial` | logical; if FALSE, initial parameter are taken from model; if TRUE, initial values of model are ignored and taken from variogram cloud: nugget: `mean(y)/2`, sill: `mean(y)/2`, range `median(h0)/4` with `y` the semivariance cloud value and `h0` the distances
`cutoff` | maximum distance up to which point pairs are taken into consideration
`plot` | logical; if TRUE, a plot is returned with variogram cloud and fitted model; else, the fitted model is returned.

### Value

an object of class "variogramModel"; see fit.variogram; if `plot` is TRUE, a plot is returned instead.

### Note

Inspired by the code of Mihael Drinovac, which was again inspired by code from Ernst Glatzer, author of package vardiag.

### Author(s)

Edzer Pebesma

### References

Mueller, W.G., 1999: Least-squares fitting from the variogram cloud. Statistics \& Probability Letters, 43, 93-98.

Mueller, W.G., 2007: Collecting Spatial Data. Springer, Heidelberg.

### See Also

fit.variogram,

### Examples

    library(sp)
    data(meuse)
    coordinates(meuse) = ~x+y
    ## Not run:
    fit.variogram.gls(log(zinc)~1, meuse[1:40,], vgm(1, "Sph", 900,1))

    ## End(Not run)

[Package gstat version 2.0-3 Index]