geoR: image.grf – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

image.grf

Image, Contour or Perspective Plot of Simulated Gaussian Random Field

Description

Methods for image, contour or perspective plot of a realisation of a Gaussian random field, simulated using the function grf.

Usage

## S3 method for class 'grf'
image(x, sim.number = 1, borders, x.leg, y.leg, ...)
## S3 method for class 'grf'
contour(x, sim.number = 1, borders, filled = FALSE, ...)
## S3 method for class 'grf'
persp(x, sim.number = 1, borders, ...)

Arguments

`x`	an object of the class `grf`, typically an output of the function `grf`.
`sim.number`	simulation number. Indicates the number of the simulation top be plotted. Only valid if the object contains more than one simulation. Defaults to 1.
`borders`	optional. Typically a two coluns matrix especifying a polygon. Points outside the borders will be set no `NA`
`x.leg, y.leg`	limits for the legend in the horizontal and vertical directions.
`filled`	logical. If `FALSE` the function `contour` is used otherwise `filled.contour`. Defaults to `FALSE`.
`...`	further arguments to be passed to the functions `image`, `contour` or `persp`.

Value

An image or perspective plot is produced on the current graphics device. No values are returned.

Author(s)

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

References

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

Examples

# generating 4 simulations of a Gaussian random field
sim <- grf(441, grid="reg", cov.pars=c(1, .25), nsim=4)
op <- par(no.readonly = TRUE)
par(mfrow=c(2,2), mar=c(3,3,1,1), mgp = c(2,1,0))
for (i in 1:4)
  image(sim, sim.n=i)
par(op)

geoR

Analysis of Geostatistical Data

v1.8-1

GPL (>= 2)

Authors

Paulo J. Ribeiro Jr [aut, cre] <paulojus@ufpr.br>, Peter J. Diggle [aut, cre] <p.diggle@lancaster.ac.uk> Ole Christensen [ctb], Martin Schlather [ctb], Roger Bivand [ctb], Brian Ripley [ctb]

Initial release

2020-02-08