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>.

Version: 1.0-0
Depends: R (≥ 3.5.0), mboost (≥ 2.9-0)
Imports: methods, graphics, grDevices, utils, stats, Matrix, gamboostLSS (≥ 2.0-0), stabs, mgcv, MASS, zoo
Suggests: fda, fields, ggplot2, maps, mapdata, knitr, refund, testthat
Published: 2020-09-08
Author: Sarah Brockhaus [aut], David Ruegamer [aut, cre], Almond Stoecker [aut], Torsten Hothorn [ctb], with contributions by many others (see inst/CONTRIBUTIONS) [ctb]
Maintainer: David Ruegamer <david.ruegamer at gmail.com>
BugReports: https://github.com/boost-R/FDboost/issues
License: GPL-2
URL: https://github.com/boost-R/FDboost
NeedsCompilation: no
Citation: FDboost citation info
Materials: NEWS
In views: FunctionalData
CRAN checks: FDboost results

Downloads:

Reference manual: FDboost.pdf
Vignettes: FDboost FLAM Canada
FDboost FLAM fuel
FDboost FLAM viscosity
Package source: FDboost_1.0-0.tar.gz
Windows binaries: r-devel: FDboost_1.0-0.zip, r-release: FDboost_1.0-0.zip, r-oldrel: FDboost_1.0-0.zip
macOS binaries: r-release: FDboost_1.0-0.tgz, r-oldrel: FDboost_1.0-0.tgz
Old sources: FDboost archive

Reverse dependencies:

Reverse suggests: mlr

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