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.

Examples

Run this code

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))))

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