Predict Method for a CQO fit
Predicted values based on a constrained quadratic ordination (CQO) object.
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, ...)object |
Object of class inheriting from |
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 |
deriv |
Derivative. Currently only 0 is handled. |
varI.latvar, refResponse |
Arguments passed into |
... |
Currently undocumented. |
Obtains predictions from a fitted CQO object. Currently there are lots of limitations of this function; it is unfinished.
See predictvglm.
This function is not robust and has not been checked fully.
T. W. Yee
Yee, T. W. (2004). A new technique for maximum-likelihood canonical Gaussian ordination. Ecological Monographs, 74, 685–701.
## Not run: 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))))
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.