Functional MSE

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Description

Calculates the functional MSE for a fitted FDboost-object

Usage

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

Arguments

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 ∑_i (Y_i(t) - \bar{Y})^2 dt \approx G^{-1} n^{-1} ∑_g ∑_i (Y_i(t_g) - \bar{Y})^2

root

take the square root of the MSE

...

currently not used

Details

Formula to calculate MSE over time, overTime=TRUE:
MSE(t) = n^{-1} ∑_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} ∑_g (Y_i(t_g) - \hat{Y}_i(t_g))^2

Value

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

Note

breaks cannot be changed in the case the bsignal() is used over the same domain as the response! In that case you would have to rename the index of the response or that of the covariates.

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