| FDboost-package | FDboost: Boosting Functional Regression Models | 
| %A% | Kronecker product or row tensor product of two base-learners with anisotropic penalty | 
| %A0% | Kronecker product or row tensor product of two base-learners with anisotropic penalty | 
| %Xa0% | Kronecker product or row tensor product of two base-learners with anisotropic penalty | 
| %Xc% | Constrained row tensor product | 
| anisotropic_Kronecker | Kronecker product or row tensor product of two base-learners with anisotropic penalty | 
| applyFolds | Cross-Validation and Bootstrapping over Curves | 
| bbsc | Constrained Base-learners for Scalar Covariates | 
| bconcurrent | Base-learners for Functional Covariates | 
| bfpc | Base-learners for Functional Covariates | 
| bhist | Base-learners for Functional Covariates | 
| bhistx | Base-learners for Functional Covariates | 
| birthDistribution | Densities of live births in Germany | 
| bolsc | Constrained Base-learners for Scalar Covariates | 
| bootstrapCI | Function to compute bootstrap confidence intervals | 
| brandomc | Constrained Base-learners for Scalar Covariates | 
| bsignal | Base-learners for Functional Covariates | 
| clr | Clr and inverse clr transformation | 
| coef.FDboost | Coefficients of boosted functional regression model | 
| cvLong | Cross-Validation and Bootstrapping over Curves | 
| cvMa | Cross-Validation and Bootstrapping over Curves | 
| cvrisk.FDboost | Cross-Validation and Bootstrapping over Curves | 
| cvrisk.FDboostLSS | Cross-validation for FDboostLSS | 
| emotion | EEG and EMG recordings in a computerised gambling study | 
| extract.blg | Extract information of a base-learner | 
| factorise | Factorize tensor product model | 
| factorize | Factorize tensor product model | 
| factorize.FDboost | Factorize tensor product model | 
| FDboost | Model-based Gradient Boosting for Functional Response | 
| FDboostLSS | Model-based Gradient Boosting for Functional GAMLSS | 
| FDboost_fac-class | 'FDboost_fac' S3 class for factorized FDboost model components | 
| FDboost_package | FDboost: Boosting Functional Regression Models | 
| fitted.FDboost | Fitted values of a boosted functional regression model | 
| fuelSubset | Spectral data of fossil fuels | 
| funMRD | Functional MRD | 
| funMSE | Functional MSE | 
| funplot | Plot functional data with linear interpolation of missing values | 
| funRsquared | Functional R-squared | 
| getArgvals | Generic functions to asses attributes of functional data objects | 
| getArgvals.hmatrix | Extract attributes of hmatrix | 
| getArgvalsLab | Generic functions to asses attributes of functional data objects | 
| getArgvalsLab.hmatrix | Extract attributes of hmatrix | 
| getId | Generic functions to asses attributes of functional data objects | 
| getId.hmatrix | Extract attributes of hmatrix | 
| getIdLab | Generic functions to asses attributes of functional data objects | 
| getIdLab.hmatrix | Extract attributes of hmatrix | 
| getTime | Generic functions to asses attributes of functional data objects | 
| getTime.hmatrix | Extract attributes of hmatrix | 
| getTimeLab | Generic functions to asses attributes of functional data objects | 
| getTimeLab.hmatrix | Extract attributes of hmatrix | 
| getX | Generic functions to asses attributes of functional data objects | 
| getX.hmatrix | Extract attributes of hmatrix | 
| getXLab | Generic functions to asses attributes of functional data objects | 
| getXLab.hmatrix | Extract attributes of hmatrix | 
| hmatrix | A S3 class for univariate functional data on a common grid | 
| integrationWeights | Functions to compute integration weights | 
| integrationWeightsLeft | Functions to compute integration weights | 
| is.hmatrix | Test to class of hmatrix | 
| mstop.validateFDboost | Methods for objects of class validateFDboost | 
| o_control | Function to control estimation of smooth offset | 
| package-FDboost | FDboost: Boosting Functional Regression Models | 
| plot.bootstrapCI | Methods for objects of class bootstrapCI | 
| plot.FDboost | Plot the fit or the coefficients of a boosted functional regression model | 
| plot.FDboost_fac | Prediction and plotting for factorized FDboost model components | 
| plot.validateFDboost | Methods for objects of class validateFDboost | 
| plotPredCoef | Methods for objects of class validateFDboost | 
| plotPredicted | Plot the fit or the coefficients of a boosted functional regression model | 
| plotResiduals | Plot the fit or the coefficients of a boosted functional regression model | 
| predict.FDboost | Prediction for boosted functional regression model | 
| predict.FDboost_fac | Prediction and plotting for factorized FDboost model components | 
| print.bootstrapCI | Methods for objects of class bootstrapCI | 
| print.FDboost | Print and summary of a boosted functional regression model | 
| print.validateFDboost | Methods for objects of class validateFDboost | 
| residuals.FDboost | Residual values of a boosted functional regression model | 
| reweightData | Function to Reweight Data | 
| stabsel.FDboost | Stability Selection | 
| subset_hmatrix | Subsets hmatrix according to an index | 
| summary.FDboost | Print and summary of a boosted functional regression model | 
| truncateTime | Function to truncate time in functional data | 
| update.FDboost | Function to update FDboost objects | 
| validateFDboost | Cross-Validation and Bootstrapping over Curves | 
| viscosity | Viscosity of resin over time | 
| wide2long | Transform id and time of wide format into long format | 
| [.hmatrix | Extract or replace parts of a hmatrix-object | 
| _PACKAGE | FDboost: Boosting Functional Regression Models |