predict.qrrvglm {VGAM}R Documentation

Predict Method for a CQO fit

Description

Predicted values based on a constrained quadratic ordination (CQO) object.

Usage

predict.qrrvglm(object, newdata=NULL,
                type=c("link", "response", "lv", "terms"),
                se.fit=FALSE, deriv=0, dispersion=NULL,
                extra=object@extra, varlvI = FALSE, reference = NULL, ...)

Arguments

object Object of class inheriting from "qrrvglm".
newdata An optional data frame in which to look for variables with which to predict. If omitted, the fitted linear predictors are used.
type, se.fit, dispersion, extra See predict.vglm.
deriv Derivative. Currently only 0 is handled.
varlvI, reference Arguments passed into Coef.qrrvglm.
... Currently undocumented.

Details

Obtains predictions from a fitted CQO object. Currently there are lots of limitations of this function; it is unfinished.

Value

See predict.vglm.

Note

This function is not robust and has not been checked fully.

Author(s)

T. W. Yee

References

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

See Also

cqo.

Examples

data(hspider)
hspider[,1:6]=scale(hspider[,1:6]) # Standardize the environmental variables
set.seed(1234)
p1 = cqo(cbind(Alopacce, Alopcune, Alopfabr, Arctlute, Arctperi, Auloalbi,
               Pardlugu, Pardmont, Pardnigr, Pardpull, Trocterr, Zoraspin) ~
         WaterCon + BareSand + FallTwig + CoveMoss + CoveHerb + ReflLux,
         fam=poissonff, data=hspider, Crow1positive=FALSE, ITol=TRUE)
sort(p1@misc$deviance.Bestof) # A history of all the iterations

predict(p1)[1:3,]

# The following should be all zeros
max(abs(predict(p1, new=hspider[1:3,]) - predict(p1)[1:3,]))
max(abs(predict(p1, new=hspider[1:3,], type="res") - fitted(p1)[1:3,]))

[Package VGAM version 0.7-7 Index]