Takes smooth objects produced by smooth.construct methods and obtains the matrix mapping
the parameters associated with such a smooth to the predicted values of the smooth at a set of new covariate values.
In practice this method is often called via the wrapper function PredictMat.
Predict.matrix(object,data)
Predict.matrix2(object,data)is a smooth object produced by a smooth.construct method function. The object
contains all the information required to specify the basis for a term of its class, and this information is
used by the appropriate Predict.matrix function to produce a prediction matrix for new covariate values.
Further details are given in smooth.construct.
A data frame containing the values of the (named) covariates at which the smooth term is to be
evaluated. Exact requirements are as for smooth.construct and smooth.construct2
A matrix which will map the parameters associated with the smooth to the vector of values of the smooth
evaluated at the covariate values given in object. If the smooth class
is one which generates offsets the corresponding offset is returned as
attribute "offset" of the matrix.
Smooth terms in a GAM formula are turned into smooth specification objects of
class xx.smooth.spec during processing of the formula. Each of these objects is
converted to a smooth object using an appropriate smooth.construct function. The Predict.matrix
functions are used to obtain the matrix that will map the parameters associated with a smooth term to
the predicted values for the term at new covariate values.
Note that new smooth classes can be added by writing a new smooth.construct method function and a
corresponding Predict.matrix method function: see the example code provided for
smooth.construct for details.
Wood S.N. (2017) Generalized Additive Models: An Introduction with R (2nd edition). Chapman and Hall/CRC Press.
# NOT RUN {
# See smooth.construct examples
# }
Run the code above in your browser using DataLab