plotqrrvglm {VGAM}R Documentation

Model Diagnostic Plots for QRR-VGLMs

Description

The residuals of a QRR-VGLM are plotted for model diagnostic purposes.

Usage

plotqrrvglm(object, 
            rtype = c("pearson", "response", "deviance", "working"), 
            ask = FALSE, 
            main = paste(Rtype, "residuals vs latent variable(s)"), 
            xlab = "Latent Variable", 
            ITolerances = object@control$EqualTolerances, ...)

Arguments

object An object of class "qrrvglm".
rtype Character string giving residual type. By default, the first one is chosen.
ask Logical. If TRUE, the user is asked to hit the return key for the next plot.
main Character string giving the title of the plot.
xlab Character string giving the x-axis caption.
ITolerances Logical. This argument is fed into Coef(object, ITolerances=ITolerances).
... Other plotting arguments (see par).

Details

Plotting the residuals can be potentially very useful for checking that the model fit is adequate.

Value

The original object.

Note

An ordination plot of a QRR-VGLM can be obtained by lvplot.qrrvglm.

Author(s)

Thomas W. Yee

References

Yee, T. W. (2004) A new technique for maximum-likelihood canonical Gaussian ordination. Ecological Monographs, 74, 685–701.

See Also

lvplot.qrrvglm, cqo.

Examples

## Not run: 
# QRR-VGLM on the hunting spiders data
# This is computationally expensive
data(hspider)
set.seed(111)  # This leads to the global solution
# hspider[,1:6]=scale(hspider[,1:6]) # Standardize the environmental variables
p1 = cqo(cbind(Alopacce, Alopcune, Alopfabr, Arctlute, Arctperi,
               Auloalbi, Pardlugu, Pardmont, Pardnigr, Pardpull,
               Trocterr, Zoraspin) ~
         WaterCon + BareSand + FallTwig + CoveMoss + CoveHerb + ReflLux,
         fam = quasipoissonff, data = hspider, Crow1positive=FALSE)
par(mfrow=c(3,4)) 
plot(p1, rtype="d", col="blue", pch=4, las=1)
## End(Not run)

[Package VGAM version 0.7-7 Index]