VGAM (version 1.1-14)

plotqrrvglm: Model Diagnostic Plots for QRR-VGLMs

Description

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

Usage

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

Value

The original object.

Details

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

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

if (FALSE) {
# QRR-VGLM on the hunting spiders data
# This is computationally expensive
set.seed(111)  # This leads to the global solution
hspider[, 1:6] <- scale(hspider[, 1:6])  # Standardize environ vars
p1 <- cqo(cbind(Alopacce, Alopcune, Alopfabr, Arctlute, Arctperi,
                Auloalbi, Pardlugu, Pardmont, Pardnigr, Pardpull,
                Trocterr, Zoraspin) ~
          WaterCon + BareSand + FallTwig + CoveMoss + CoveHerb + ReflLux,
          poissonff, data = hspider, Crow1positive = FALSE)
par(mfrow = c(3, 4))
plot(p1, rtype = "response", col = "blue", pch = 4, las = 1, main = "")
}