FDboost (version 1.0-0)

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.


# S3 method for FDboost
  raw = FALSE,
  which = NULL,
  computeCoef = TRUE,
  returnData = FALSE,
  n1 = 40,
  n2 = 40,
  n3 = 20,
  n4 = 10,



a fitted FDboost-object


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.


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.


defaults to TRUE, if FALSE only the names of the terms are returned


return the dataset which is used to get the coefficient estimates as predictions, see Details.


see below


see below


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.


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


other arguments, not used.


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.


If raw = FALSE the function coef.FDboost generates adequate dummy data and uses the function predict.FDboost to compute the estimated coefficient functions.