Package: FDboost 1.1-1

David Ruegamer

FDboost: Boosting Functional Regression Models

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>.

Authors:Sarah Brockhaus [aut], David Ruegamer [aut, cre], Almond Stoecker [aut], Torsten Hothorn [ctb], with contributions by many others [ctb]

FDboost_1.1-1.tar.gz
FDboost_1.1-1.zip(r-4.5)FDboost_1.1-1.zip(r-4.4)FDboost_1.1-1.zip(r-4.3)
FDboost_1.1-1.tgz(r-4.4-any)FDboost_1.1-1.tgz(r-4.3-any)
FDboost_1.1-1.tar.gz(r-4.5-noble)FDboost_1.1-1.tar.gz(r-4.4-noble)
FDboost_1.1-1.tgz(r-4.4-emscripten)FDboost_1.1-1.tgz(r-4.3-emscripten)
FDboost.pdf |FDboost.html✨
FDboost/json (API)
NEWS

# Install 'FDboost' in R:
install.packages('FDboost', repos = c('https://boost-r.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/boost-r/fdboost/issues

Datasets:

On CRAN:

boostingboosting-algorithmsfunction-on-function-regressionfunction-on-scalar-regressionmachine-learningscalar-on-function-regressionvariable-selection

7.56 score 16 stars 94 scripts 945 downloads 3 mentions 45 exports 18 dependencies

Last updated 7 months agofrom:6c172c57d3. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-winNOTENov 05 2024
R-4.5-linuxNOTENov 05 2024
R-4.4-winOKNov 05 2024
R-4.4-macOKNov 05 2024
R-4.3-winOKNov 05 2024
R-4.3-macOKNov 05 2024

Exports:%A%%A0%%Xa0%%Xc%applyFoldsbbscbconcurrentbfpcbhistbhistxbolscbootstrapCIbrandomcbsignalclrcvLongcvMafactorizeFDboostFDboostLSSfunMRDfunMSEfunplotfunRsquaredgetArgvalsgetArgvalsLabgetIdgetIdLabgetTimegetTimeLabgetXgetXLabhmatrixintegrationWeightsintegrationWeightsLeftis.hmatrixo_controlplotPredCoefplotPredictedplotResidualsreweightDatasubset_hmatrixtruncateTimevalidateFDboostwide2long

Dependencies:FormulagamboostLSSinumlatticelibcoinMASSMatrixmboostmgcvmvtnormnlmennlspartykitquadprogrpartstabssurvivalzoo

FDboost density-on-scalar births

Rendered fromdensity-on-scalar_birth.Rnwusingknitr::knitron Nov 05 2024.

Last update: 2022-07-13
Started: 2021-10-22

FDboost FLAM Canada

Rendered fromFLAM_canada.Rnwusingknitr::knitron Nov 05 2024.

Last update: 2020-09-08
Started: 2016-09-20

FDboost FLAM fuel

Rendered fromFLAM_fuel.Rnwusingknitr::knitron Nov 05 2024.

Last update: 2020-09-08
Started: 2016-09-20

FDboost FLAM viscosity

Rendered fromFLAM_viscosity.Rnwusingknitr::knitron Nov 05 2024.

Last update: 2020-09-08
Started: 2016-09-20

Readme and manuals

Help Manual

Help pageTopics
FDboost: Boosting Functional Regression ModelsFDboost-package FDboost_package package-FDboost _PACKAGE
Extract or replace parts of a hmatrix-object[.hmatrix
Constrained row tensor product%Xc%
Kronecker product or row tensor product of two base-learners with anisotropic penalty%A% %A0% %Xa0% anisotropic_Kronecker
Cross-Validation and Bootstrapping over CurvesapplyFolds cvLong cvMa cvrisk.FDboost
Constrained Base-learners for Scalar Covariatesbbsc bolsc brandomc
Base-learners for Functional Covariatesbhistx
Densities of live births in GermanybirthDistribution
Function to compute bootstrap confidence intervalsbootstrapCI
Base-learners for Functional Covariatesbconcurrent bfpc bhist bsignal
Clr and inverse clr transformationclr
Coefficients of boosted functional regression modelcoef.FDboost
Cross-validation for FDboostLSScvrisk.FDboostLSS
EEG and EMG recordings in a computerised gambling studyemotion
Extract information of a base-learnerextract.blg
Factorize tensor product modelfactorise factorize factorize.FDboost
Model-based Gradient Boosting for Functional ResponseFDboost
`FDboost_fac` S3 class for factorized FDboost model componentsFDboost_fac-class
Model-based Gradient Boosting for Functional GAMLSSFDboostLSS
Fitted values of a boosted functional regression modelfitted.FDboost
Spectral data of fossil fuelsfuelSubset
Functional MRDfunMRD
Functional MSEfunMSE
Plot functional data with linear interpolation of missing valuesfunplot
Functional R-squaredfunRsquared
Generic functions to asses attributes of functional data objectsgetArgvals getArgvalsLab getId getIdLab getTime getTimeLab getX getXLab
Extract attributes of hmatrixgetArgvals.hmatrix getArgvalsLab.hmatrix getId.hmatrix getIdLab.hmatrix getTime.hmatrix getTimeLab.hmatrix getX.hmatrix getXLab.hmatrix
A S3 class for univariate functional data on a common gridhmatrix
Functions to compute integration weightsintegrationWeights integrationWeightsLeft
Test to class of hmatrixis.hmatrix
Methods for objects of class validateFDboostmstop.validateFDboost plot.validateFDboost plotPredCoef print.validateFDboost
Function to control estimation of smooth offseto_control
Methods for objects of class bootstrapCIplot.bootstrapCI print.bootstrapCI
Plot the fit or the coefficients of a boosted functional regression modelplot.FDboost plotPredicted plotResiduals
Prediction for boosted functional regression modelpredict.FDboost
Prediction and plotting for factorized FDboost model componentsplot.FDboost_fac predict.FDboost_fac
Residual values of a boosted functional regression modelresiduals.FDboost
Function to Reweight DatareweightData
Stability Selectionstabsel.FDboost
Subsets hmatrix according to an indexsubset_hmatrix
Print and summary of a boosted functional regression modelprint.FDboost summary.FDboost
Function to truncate time in functional datatruncateTime
Function to update FDboost objectsupdate.FDboost
Cross-Validation and Bootstrapping over CurvesvalidateFDboost
Viscosity of resin over timeviscosity
Transform id and time of wide format into long formatwide2long