Calculates the functional MSE for a fitted FDboost-object

```
funMSE(
object,
overTime = TRUE,
breaks = object$yind,
global = FALSE,
relative = FALSE,
root = FALSE,
...
)
```

object

fitted FDboost-object

overTime

per default the functional R-squared is calculated over time
if `overTime=FALSE`

, the R-squared is calculated per curve

breaks

an optional vector or number giving the time-points at which the model is evaluated. Can be specified as number of equidistant time-points or as vector of time-points. Defaults to the index of the response in the model.

global

logical. defaults to `FALSE`

,
if TRUE the global R-squared like in a normal linear model is calculated

relative

logical. defaults to `FALSE`

. If `TRUE`

the MSE is standardized
by the global variance of the response
\( n^{-1} \int \sum_i (Y_i(t) - \bar{Y})^2 dt \approx G^{-1} n^{-1} \sum_g \sum_i (Y_i(t_g) - \bar{Y})^2 \)

root

take the square root of the MSE

...

currently not used

Returns a vector with the calculated MSE and some extra information in attributes.

Formula to calculate MSE over time, `overTime=TRUE`

:
\( MSE(t) = n^{-1} \sum_i (Y_i(t) - \hat{Y}_i(t))^2 \)

Formula to calculate MSE over subjects, `overTime=FALSE`

:
\( MSE_i = \int (Y_i(t) - \hat{Y}_i(t))^2 dt \approx G^{-1} \sum_g (Y_i(t_g) - \hat{Y}_i(t_g))^2\)