VGAM (version 1.1-8)

predictqrrvglm: Predict Method for a CQO fit

Description

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

Usage

predictqrrvglm(object, newdata = NULL,
    type = c("link", "response", "latvar", "terms"),
    se.fit = FALSE, deriv = 0, dispersion = NULL,
    extra = object@extra, varI.latvar = FALSE, refResponse = NULL, ...)

Value

See predictvglm.

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 predictvglm.

deriv

Derivative. Currently only 0 is handled.

varI.latvar, refResponse

Arguments passed into Coef.qrrvglm.

...

Currently undocumented.

Author

T. W. Yee

Details

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

References

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

See Also

cqo, calibrate.qrrvglm.

Examples

if (FALSE)  set.seed(1234)
hspider[, 1:6] <- scale(hspider[, 1:6])  # Standardize the X 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, I.toler = TRUE)
sort(deviance(p1, history = TRUE))  # A history of all the iterations
head(predict(p1))

# The following should be all 0s:
max(abs(predict(p1, newdata = head(hspider)) - head(predict(p1))))
max(abs(predict(p1, newdata = head(hspider), type = "res")-head(fitted(p1))))