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
function for `predict.mboost()`

```
# S3 method for FDboost
predict(object, newdata = NULL, which = NULL, toFDboost = TRUE, ...)
```

object

a fitted `FDboost`

-object

newdata

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 `newdata`

is 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.

which

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.

toFDboost

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 `predict.mboost()`

.

a matrix or list of predictions depending on values of unlist and which

`FDboost`

for the model fit
and `plotPredicted`

for a plot of the observed values and their predictions.