# coef.FDboost

##### Coefficients of boosted functional regression model

Takes a fitted `FDboost`

-object produced by `FDboost()`

and
returns estimated coefficient functions/surfaces \(\beta(t), \beta(s,t)\) and
estimated smooth effects \(f(z), f(x,z)\) or \(f(x, z, t)\).
Not implemented for smooths in more than 3 dimensions.

##### Usage

```
# S3 method for FDboost
coef(object, raw = FALSE, which = NULL,
computeCoef = TRUE, returnData = FALSE, n1 = 40, n2 = 40, n3 = 20,
n4 = 10, ...)
```

##### Arguments

- object
a fitted

`FDboost`

-object- raw
logical defaults to

`FALSE`

. If`raw = FALSE`

for each effect the estimated function/surface is calculated. If`raw = TRUE`

the coefficients of the model are returned.- which
a subset of base-learners for which the coefficients should be computed (numeric vector), defaults to NULL which is the same as

`which=1:length(object$baselearner)`

. In the special case of`which=0`

, only the coefficients of the offset are returned.- computeCoef
defaults to

`TRUE`

, if`FALSE`

only the names of the terms are returned- returnData
return the dataset which is used to get the coefficient estimates as predictions, see Details.

- n1
see below

- n2
see below

- n3
n1, n2, n3 give the number of grid-points for 1-/2-/3-dimensional smooth terms used in the marginal equidistant grids over the range of the covariates at which the estimated effects are evaluated.

- n4
gives the number of points for the third dimension in a 3-dimensional smooth term

- ...
other arguments, not used.

##### Details

If `raw = FALSE`

the function `coef.FDboost`

generates adequate dummy data
and uses the function `predict.FDboost`

to
compute the estimated coefficient functions.

##### Value

If `raw = FALSE`

, a list containing

`offset`

a list with plot information for the offset.`smterms`

a named list with one entry for each smooth term in the model. Each entry contains`x, y, z`

the unique grid-points used to evaluate the smooth/coefficient function/coefficient surface`xlim, ylim, zlim`

the extent of the x/y/z-axes`xlab, ylab, zlab`

the names of the covariates for the x/y/z-axes`value`

a vector/matrix/list of matrices containing the coefficient values`dim`

the dimensionality of the effect`main`

the label of the smooth term (a short label)

If `raw = TRUE`

, a list containing the estimated spline coefficients.

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