This is a user friendly method to compute predictions from GeDS objects.
# S3 method for GeDS
predict(object, newdata, type = c("response", "link", "terms"), n = 3L, ...)A numeric vector corresponding to the predicted values (if
type = "link" or type = "response"). If type = "terms" a
numeric matrix with a column per term.
the GeDS-class object for which the
computation of the predicted values is required.
an optional data.frame, list or
environment containing values of the independent variables for which
predicted values of the predictor model (including the GeDS and the
parametric components) should be computed. If left empty the values are
extracted from the object x itself.
character string indicating the type of prediction required. By
default it is equal to "response", i.e. the result is on the scale of
the response variable. See details for the other options.
integer value (2, 3 or 4) specifying the order (\(=\) degree
\( + 1\)) of the GeDS fit whose predicted values should be computed. By
default equal to 3L. Non-integer values will be passed to the function
as.integer.
potentially further arguments (required by the definition of the generic function). They are ignored, but with a warning.
This is a method for the function predict that allows
the user to handle GeDS-Class objects.
In analogy with the function predict.glm in the
stats package, the user can specify the scale on which the predictions
should be computed through the argument type. If the predictions are
required to be on the scale of the response variable, the user should set
type = "response", which is the default. Alternatively if one wants
the predictions to be on the predictor scale, it is necessary to set
type = "link".
By specifying type = "terms", it is possible to inspect the predicted
values separately for each single independent variable which enter either the
GeD spline component or the parametric component of the predictor model. In
this case the returned result is a matrix whose columns correspond to the
terms supplied via newdata or extracted from the object.
As GeDS objects contain three different fits (linear, quadratic and cubic),
it is possible to specify the order for which GeDS predictions are required
via the input argument n.
predict for the standard definition;
GGeDS for examples.