Obtains various types of predictions/fitted values for heteroscedastic extended logistic regression (HXLR) models.
# S3 method for hxlr
predict(object, newdata = NULL, type = c("class", "probability",
"cumprob", "location", "scale"), thresholds = object$thresholds,
na.action = na.pass, ...)
# S3 method for hxlr
fitted(object, type = c("class", "probability",
"cumprob", "location", "scale"), ...)For type "prob" a matrix with number of intervals (= number of
thresholds + 1) columns is produced. Each row corresponds to a row in newdata
and contains the predicted probabilities to fall in the corresponding interval.
For type "cumprob" a matrix with number of thresholds columns is
produced. Each row corresponds to a row in newdata and contains the
predicted probabilities to fall below the corresponding threshold.
For types "class", "location", and "scale" a vector is
returned respectively with either the most probable categories ("class")
or the location ("location") or scale (scale) of the latent
distribution.
an object of class "hxlr".
an optional data frame in which to look for variables with which to predict.
type of prediction: "probability" returns a data frame
with category probabilities, "cumprob" returns cumulative
probabilities, "location" and "scale" return the location and
scale of the predicted latent distribution respectively, and "class"
returns the category with the highest probability. Default is
"class".
optional thresholds used for defining the thresholds for
types "probability", "cumprob", and "class". Can differ
from thresholds used for fitting. If omitted, the same thresholds as for
fitting are used.
A function which indicates what should happen when the data
contain NAs. Default is na.pass
further arguments passed to or from other methods.
hxlr