Prediction for boosted functional regression model
Takes a fitted
FDboost-object produced by
FDboost() and produces
predictions given a new set of values for the model covariates or the original
values used for the model fit. This is a wrapper
# S3 method for FDboost predict(object, newdata = NULL, which = NULL, toFDboost = TRUE, ...)
a named list or a data frame containing the values of the model covariates at which predictions are required. If this is not provided then predictions corresponding to the original data are returned. If
newdatais provided then it should contain all the variables needed for prediction, in the format supplied to
FDboost, i.e., functional predictors must be supplied as matrices with each row corresponding to one observed function.
a subset of base-learners to take into account for computing predictions or coefficients. If which is given (as an integer vector corresponding to base-learners) a list is returned.
logical, defaults to
TRUE. In case of regular response in wide format (i.e. response is supplied as matrix): should the predictions be returned as matrix, or list of matrices instead of vectors
additional arguments passed on to
a matrix or list of predictions depending on values of unlist and which