Coefficients of boosted functional regression model
Coefficients of boosted functional regression model
Takes a fitted FDboost-object produced by FDboost() and returns estimated coefficient functions/surfaces β(t),β(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 class 'FDboost'coef( object, raw =FALSE, which =NULL, computeCoef =TRUE, returnData =FALSE, n1 =40, n2 =40, n3 =20, n4 =10,...)
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.
Returns
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.
Details
If raw = FALSE the function coef.FDboost generates adequate dummy data and uses the function predict.FDboost to compute the estimated coefficient functions.