coef.FDboost: Coefficients of boosted functional regression model

Description

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,
  ...
)

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.

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.