| 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 |
| 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 |
| 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 |
| FDboost | Model-based Gradient Boosting for Functional Response |
| FDboostLSS | Model-based Gradient Boosting for Functional GAMLSS |
| 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.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 |
| 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 |