show.vgms {gstat}R Documentation

Plot Variogram Model Functions

Description

Creates a trellis plot for a range of variogram models, possibly with nugget; and optionally a set of Matern models with varying smoothness.

Usage

show.vgms(min = 1e-12 * max, max = 3, n = 50, sill = 1, range = 1,
    models = as.character(vgm()$short[c(1:17)]), nugget = 0, kappa.range = 0.5,
	plot = TRUE, ..., as.groups = FALSE)

Arguments

min

numeric; start distance value for semivariance calculation beyond the first point at exactly zero

max

numeric; maximum distance for semivariance calculation and plotting

n

integer; number of points to calculate distance values

sill

numeric; (partial) sill(s) of the variogram model

range

numeric; range(s) of the variogram model

models

character; variogram model(s) to be plotted

nugget

numeric; nugget component(s) for variogram models

kappa.range

numeric; if this is a vector with more than one element, only a range of Matern models is plotted with these kappa values

plot

logical; if TRUE, a plot is returned with the models specified; if FALSE, the data prepared for this plot is returned

...

passed on to the call to xyplot

as.groups

logical; if TRUE, different models are plotted with different lines in a single panel, else, in one panel per model

Value

returns a (Trellis) plot of the variogram models requested; see examples. I do currently have strong doubts about the “correctness” of the “Hol” model. The “Spl” model does seem to need a very large range value (larger than the study area?) to be of some value.

If plot is FALSE, a data frame with the data prepared to plot is being returned.

Note

the min argument is supplied because the variogram function may be discontinuous at distance zero, surely when a positive nugget is present.

Author(s)

Edzer Pebesma

References

http://www.gstat.org

See Also

vgm, variogramLine,

Examples

show.vgms()
show.vgms(models = c("Exp", "Mat", "Gau"), nugget = 0.1)
# show a set of Matern models with different smoothness:
show.vgms(kappa.range = c(.1, .2, .5, 1, 2, 5, 10), max = 10)
# show a set of Exponential class models with different shape parameter:
show.vgms(kappa.range = c(.05, .1, .2, .5, 1, 1.5, 1.8, 1.9, 2), models = "Exc", max = 10)
# show a set of models with different shape parameter of M. Stein's representation of the Matern:
show.vgms(kappa.range = c(.01, .02, .05, .1, .2, .5, 1, 2, 5, 1000), models = "Ste", max = 2)


[Package gstat version 2.1-1 Index]