lines.variomodel {geoR}R Documentation

Adds a Line with a Variogram Model to a Variogram Plot

Description

This function adds a line with a variogram model specifyed by the user to a current variogram plot. The variogram is specifyed either by passing a list with values for the variogram elements or using each argument in the function.

Usage

lines.variomodel(x, ...)
## Default S3 method:
lines.variomodel(x, cov.model, cov.pars, nugget, kappa,
                          max.dist, scaled = FALSE, ...)

Arguments

x a list with the values for the following components: cov.model, cov.pars, nugget, kappa (not aways compulsory, see argument kappa below), max.dist. This argument is optional if the other arguments in the function are provided, otherwise is compulsory.
cov.model a string with the type of the variogram function. See documentation of cov.spatial for further details.
cov.pars a vector or matrix with the values for the sill (sigmasq) and range (phi) parameters.
nugget a scalar with the value of the nugget (tausq) parameter.
kappa a scalar with the value of the smoothness (kappa) parameters. Only required if cov.model is one of the following: "matern", "powered.exponential", "cauchy" and "gneiting.matern"
max.dist maximum distance (x-axis) to compute and draw the line representing the variogram model. The default is the distance given by obj$max.dist.
scaled logical. If TRUE the total sill in the plot is equals to 1.
... arguments to be passed to the function curve.

Details

Adds a line with a variogram model to a plot. In conjuction with plot.variogram can be used for instance to compare sample variograms against fitted models returned by variofit and/or likfit.

Value

A line with a variogram model is added to a plot on the current graphics device. No values are returned.

Author(s)

Paulo Justiniano Ribeiro Jr. Paulo.Ribeiro@est.ufpr.br,
Peter J. Diggle p.diggle@lancaster.ac.uk.

References

Further information on the package geoR can be found at:
http://www.est.ufpr.br/geoR.

See Also

lines.variomodel.krige.bayes, lines.variomodel.grf, lines.variomodel.variofit, lines.variomodel.likGRF, plot.variogram, lines.variogram, variofit, likfit, curve.

Examples

data(s100)
# compute and plot empirical variogram
vario <- variog(s100, max.dist = 1)
plot(vario)
# estimate parameters
vario.wls <- variofit(vario, ini = c(1, .3), fix.nugget = TRUE)
# adds fitted model to the plot  
lines(vario.wls)
#
# Ploting different variogram models
plot(0:1, 0:1, type="n")
lines.variomodel(cov.model = "exp", cov.pars = c(.7, .25), nug = 0.3, max.dist = 1) 
# an alternative way to do this is:
my.model <- list(cov.model = "exp", cov.pars = c(.7, .25), nugget = 0.3,
max.dist = 1) 
lines.variomodel(my.model, lwd = 2)
# now adding another model
lines.variomodel(cov.m = "mat", cov.p = c(.7, .25), nug = 0.3,
                 max.dist = 1, kappa = 1, lty = 2)
[Package Contents]