# predict.FDboost

##### 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
function for `predict.mboost()`

##### Usage

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

##### Arguments

- 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()`

.

##### Value

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

##### See Also

`FDboost`

for the model fit
and `plotPredicted`

for a plot of the observed values and their predictions.

*Documentation reproduced from package FDboost, version 0.3-2, License: GPL-2*