predict.addreg.smooth {addreg} | R Documentation |
Obtains predictions from a fitted addreg.smooth
object.
## S3 method for class 'addreg.smooth'
predict(object, newdata = NULL, type = c("link", "response", "terms"),
terms = NULL, na.action = na.pass, ...)
object |
a fitted object of class inheriting from |
newdata |
optionally, a data frame in which to look for variables with which to predict. If omitted, the fitted linear predictors are used. |
type |
the type of prediction required. The default is on the scale of the linear predictors;
the alternative The value of this argument can be abbreviated. |
terms |
with |
na.action |
function determining what should be done with missing values in |
... |
further arguments passed to or from other methods. |
predict.addreg.smooth
constructs the underlying basis functions for smooth variables
in newdata
and runs predict.addreg
to obtain predictions. Note that
if values of smooth covariates in newdata
are outside the covariate space of
object
, an error will be returned.
If newdata
is omitted, the predictions are based on the data used for the fit.
In that case how cases with missing values in the original fit are treated is determined by the
na.action
argument of that fit. If na.action = na.omit
, omitted cases
will not appear in the residuals; if na.action = na.exclude
they will
appear, with residual value NA
. See also napredict
.
A vector or matrix of predictions. For type = "terms"
, this is a matrix with
a column per term, and may have an attribute "constant"
.
Variables are first looked for in newdata
and then searched for in the usual
way (which will include the environment of the formula used in the fit). A warning
will be given if the variables found are not of the same length as those in
newdata
if it was supplied.
Mark W. Donoghoe markdonoghoe@gmail.com
predict.glm
for the equivalent method for models fit using glm
.
## For an example, see example(addreg.smooth)