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

    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

    head(predict(p1))

    # The following should be all zeros
    max(abs(predict(p1, new=head(hspider)) - head(predict(p1))))
    max(abs(predict(p1, new=head(hspider), type="res") - head(fitted(p1))))

[Package VGAM version 0.7-9 Index]