Coefficients of boosted functional regression model
Takes a fitted
FDboost-object produced by
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 coef(object, raw = FALSE, which = NULL, computeCoef = TRUE, returnData = FALSE, n1 = 40, n2 = 40, n3 = 20, n4 = 10, ...)
logical defaults to
raw = FALSEfor each effect the estimated function/surface is calculated. If
raw = TRUEthe 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.
FALSEonly the names of the terms are returned
return the dataset which is used to get the coefficient estimates as predictions, see Details.
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.
raw = FALSE the function
coef.FDboost generates adequate dummy data
and uses the function
compute the estimated coefficient functions.
raw = FALSE, a list containing
offseta list with plot information for the offset.
smtermsa named list with one entry for each smooth term in the model. Each entry contains
x, y, zthe unique grid-points used to evaluate the smooth/coefficient function/coefficient surface
xlim, ylim, zlimthe extent of the x/y/z-axes
xlab, ylab, zlabthe names of the covariates for the x/y/z-axes
valuea vector/matrix/list of matrices containing the coefficient values
dimthe dimensionality of the effect
mainthe label of the smooth term (a short label)
raw = TRUE, a list containing the estimated spline coefficients.