Calculates the functional MSE for a fitted FDboost-object
funMSE(
object,
overTime = TRUE,
breaks = object$yind,
global = FALSE,
relative = FALSE,
root = FALSE,
...
)fitted FDboost-object
per default the functional R-squared is calculated over time
if overTime=FALSE, the R-squared is calculated per curve
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.
logical. defaults to FALSE,
if TRUE the global R-squared like in a normal linear model is calculated
logical. defaults to FALSE. If TRUE the MSE is standardized
by the global variance of the response
\( n^{-1} \int \sum_i (Y_i(t) - \bar{Y})^2 dt \approx G^{-1} n^{-1} \sum_g \sum_i (Y_i(t_g) - \bar{Y})^2 \)
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:
\( MSE_i = \int (Y_i(t) - \hat{Y}_i(t))^2 dt \approx G^{-1} \sum_g (Y_i(t_g) - \hat{Y}_i(t_g))^2\)