fields (version 1.2)

plot.Krig: Diagnostic and summary plots of the Krig object

Description

Plots a series of four diagnostic plots that summarize the fit from Krig.

Usage

plot.Krig(out, main=NA, digits=4, which=c(TRUE,T,T,TRUE), graphics.reset=TRUE,
...)

Arguments

out

A Krig output object.

main

Title of the plot. Default is the function call.

digits

Number of significant digits for the RMSE label.

graphics.reset

Reset to original graphics parameters after plotting. Default is TRUE.

which

A vector of 4 logical values. Controls which of the four graphs to plot.

...

Optional graphics arguments to pass to each plot.

Details

This function creates four summary plots of the Krig object. The default is to put these in a 2X2 panel. However if the screen is already divided in some other fashion the plots will just be added according to that scheme. This option is useful to compare to compare several different model fits.

The first is a scatterplot of predicted value against observed.

The second plot is "standardized" residuals against predicted value. Here we mean that the residuals are divided by the GCV estimate for sigma and multiplied by the square root of any weights that have been specified. In the case of a "correlation model" the residuals are also divided by the marginal standard deviation from this model.

The third plot are the values of the GCV function against the effective degrees of freedom. When there are replicate points several versions of the GCV function may be plotted. GCV function is with respect to the standardized data if a correlation model is specified. A vertical line indicates the minimium found.

The fourth plot is a histogram of the standardized residuals.

See Also

Krig, summary.Krig, Tps

Examples

fit<-Krig(ozone$x, ozone$y,exp.cov, theta=200)  
# fitting a surface to ozone  
# measurements 
plot(fit)