VGAM (version 1.0-4)

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, ...)

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.

Value

See predictvglm.

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.

Examples

# NOT RUN {
hspider[,1:6] <- scale(hspider[,1:6])  # Standardize the environmental vars
set.seed(1234)
# vvv p1 <- cqo(cbind(Alopacce, Alopcune, Alopfabr, Arctlute,
# vvv                 Arctperi, Auloalbi, Pardlugu, Pardmont,
# vvv                 Pardnigr, Pardpull, Trocterr, Zoraspin) ~
# vvv       WaterCon + BareSand + FallTwig + CoveMoss + CoveHerb + ReflLux,
# vvv       poissonff, data = hspider, Crow1positive = FALSE, I.tol = TRUE)
# vvv sort(deviance(p1, history = TRUE))  # A history of all the iterations

# vvv head(predict(p1))

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