Boosting Functional Regression Models
Kronecker product or row tensor product of two base-learners with anis...
Cross-Validation and Bootstrapping over Curves
Constrained Base-learners for Scalar Covariates
Base-learners for Functional Covariates
Function to compute bootstrap confidence intervals
Base-learners for Functional Covariates
Clr and inverse clr transformation
Coefficients of boosted functional regression model
Cross-validation for FDboostLSS
Extract information of a base-learner
Factorize tensor product model
FDboost: Boosting Functional Regression Models
Model-based Gradient Boosting for Functional Response
FDboost_fac
S3 class for factorized FDboost model components
Model-based Gradient Boosting for Functional GAMLSS
Fitted values of a boosted functional regression model
Functional MRD
Functional MSE
Plot functional data with linear interpolation of missing values
Functional R-squared
Extract attributes of hmatrix
Generic functions to asses attributes of functional data objects
Constrained row tensor product
A S3 class for univariate functional data on a common grid
Functions to compute integration weights
Test to class of hmatrix
Function to control estimation of smooth offset
Methods for objects of class bootstrapCI
Plot the fit or the coefficients of a boosted functional regression mo...
Methods for objects of class validateFDboost
Prediction for boosted functional regression model
Prediction and plotting for factorized FDboost model components
Residual values of a boosted functional regression model
Function to Reweight Data
Stability Selection
Extract or replace parts of a hmatrix-object
Subsets hmatrix according to an index
Print and summary of a boosted functional regression model
Function to truncate time in functional data
Function to update FDboost objects
Cross-Validation and Bootstrapping over Curves
Transform id and time of wide format into long format
Regression models for functional data, i.e., scalar-on-function, function-on-scalar and function-on-function regression models, are fitted by a component-wise gradient boosting algorithm. For a manual on how to use 'FDboost', see Brockhaus, Ruegamer, Greven (2017) <doi:10.18637/jss.v094.i10>.