plot.georob: Plot Methods for class 'georob'

In georob: Robust Geostatistical Analysis of Spatial Data

Description

The plot and lines methods for class georob plot the variogram model, estimated by (robust) restricted maximum likelihood. plot.georob computes and plots in addition the sample variogram of the (robust) regression residuals.

Usage

## S3 method for class 'georob'
plot(x, type, what = c("variogram", "covariance", "correlation"),
    plot.sv = TRUE, add = FALSE, lag.class.def, 
    xy.angle.def = c(0, 180), xz.angle.def = c(0, 180), 
    max.lag = Inf, estimator = c("mad", "qn", "ch", "matheron"), 
    mean.angle = TRUE, col, pch, lty, ...)

## S3 method for class 'georob'
lines(x, what = c("variogram", "covariance", "correlation"),
    from = 1.e-6, to, n = 501, xy.angle = 90, xz.angle = 90, 
    col = 1:length(xy.angle), pch = 1:length(xz.angle), lty = "solid", ...)

Arguments

x	an object of class georob, see georobObject.
type	the type of plot for display of the sample variogram, see plot.
what	the quantity that should be displayed. Note that plot.sv will be set to FALSE unless what == "variogram" (default).
plot.sv	logical controlling if the sample variogram of the regression residuals, hatB(s) + hatε{s} should be added to the plot (default TRUE).
add	logical controlling whether a new plot should be generated (FALSE, default) or whether the information should be added to the current plot (TRUE).
lag.class.def	a numeric scalar defining a constant bin width for grouping the lag distances or a numeric vector with the upper bounds of a set of contiguous bins.
xy.angle.def	an numeric vector defining angular classes in the horizontal plane for computing directional variograms. xy.angle.def must contain an ascending sequence of azimuth angles in degrees from north (positive clockwise to south), see sample.variogram. Omnidirectional variograms are computed with the default c(0,180).
xz.angle.def	an numeric vector defining angular classes in the x-z-plane for computing directional variograms. xz.angle.def must contain an ascending sequence of angles in degrees from zenith (positive clockwise to nadir), see sample.variogram. Omnidirectional variograms are computed with the default c(0,180).
max.lag	positive numeric defining the largest lag distance for which semivariances should be computed (default no restriction).
estimator	character keyword defining the estimator for computing the sample variogram. Possible values are: "qn": Genton's robust Qn-estimator (default, Genton, 1998), "mad": Dowd's robust MAD-estimator (Dowd, 1984), "matheron": non-robust method-of-moments estimator, "ch": robust Cressie-Hawkins estimator (Cressie and Hawkins, 1980).
mean.angle	logical controlling whether the mean lag vector (per combination of lag distance and angular class) is computed from the mean angles of all the lag vectors falling into a given class (TRUE, default) or from the mid-angles of the respective angular classes (FALSE).
from	numeric, minimal lag distance for plotting variogram models.
to	numeric, maximum lag distance for plotting variogram models (default: largest lag distance of current plot).
n	positive integer specifying the number of equally spaced lag distances for which semivariances are evaluated in plotting variogram models (default 501).
xy.angle	numeric (vector) with azimuth angles (in degrees, clockwise positive from north) in x-y-plane for which semivariances should be plotted.
xz.angle	numeric (vector) with angles in x-z-plane (in degrees, clockwise positive from zenith to south) for which semivariances should be plotted.
col	color of curves to distinguish curves relating to different azimuth angles in x-y-plane.
pch	type of plotting symbols added to lines to distinguish curves relating to different angles in x-z-plane.
lty	line type for plotting variogram models.
...	additional arguments passed to plot.sample.variogram and methods.

Author(s)

Andreas Papritz [e-mail].

See Also

georobIntro for a description of the model and a brief summary of the algorithms; georob for (robust) fitting of spatial linear models; georobObject for a description of the class georob; sample.variogram for computing sample variograms.

Examples

## Not run: 
################
## meuse data ##
################
data( meuse )

## Gaussian REML fit
r.logzn.reml <- georob(log(zinc) ~ sqrt(dist), data = meuse, locations = ~ x + y,
    variogram.model = "exponential",
    param = c( variance = 0.15, nugget = 0.05, scale = 200 ),
    tuning.psi = 1000)
summary(r.logzn.reml, correlation = TRUE)

## robust REML fit 
r.logzn.rob <- update(r.logzn.reml, tuning.psi = 1)
    
summary(r.logzn.rob, correlation = TRUE)

plot(r.logzn.reml, lag.class.def = seq( 0, 2000, by = 100 ))
lines(r.logzn.rob, col = "red")
## End(Not run)

georob documentation built on May 2, 2019, 6:53 p.m.