FDboost: Boosting Functional Regression Models
EEG and EMG recordings in a computerised gambling study
Transform id and time of wide format into long format
Cross-Validation and Bootstrapping over Curves
Functional MRD
Prediction for boosted functional regression model
Methods for objects of class validateFDboost
Extract or replace parts of a hmatrix-object
Cross-Validation and Bootstrapping over Curves
Stability Selection
Viscosity of resin over time
Extract attributes of hmatrix
Plot functional data with linear interpolation of missing values
Plot the fit or the coefficients of a boosted functional regression model
Constrained Base-learners for Scalar Covariates
Extract information of a base-learner
Fitted values of a boosted functional regression model
Methods for objects of class bootstrapCI
Subsets hmatrix according to an index
Test to class of hmatrix
Generic functions to asses attributes of functional data objects
Constrained row tensor product
Functional MSE
Function to control estimation of smooth offset
Print and summary of a boosted functional regression model
A S3 class for univariate functional data on a common grid
Functions to compute integration weights
Residual values of a boosted functional regression model
Functional R-squared
Function to Reweight Data
Function to truncate time in functional data
Function to update FDboost objects
Cross-validation for FDboostLSS
Model-based Gradient Boosting for Functional GAMLSS
Base-learners for Functional Covariates
Spectral data of fossil fuels
Kronecker product or row tensor product of two base-learners with anisotropic penalty
Function to compute bootstrap confidence intervals
Model-based Gradient Boosting for Functional Response
Base-learners for Functional Covariates
Coefficients of boosted functional regression model