CRAN/E | FDboost

FDboost

Boosting Functional Regression Models

Installation

About

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.

Citation FDboost citation info
github.com/boost-R/FDboost
Bug report File report

Key Metrics

Version 1.1-2
R ≥ 3.5.0
Published 2023-08-12 251 days ago
Needs compilation? no
License GPL-2
CRAN checks FDboost results

Downloads

Yesterday 32
Last 7 days 161 -52%
Last 30 days 1.079 -16%
Last 90 days 5.757 +2%
Last 365 days 18.854 +29%

Maintainer

Maintainer

David Ruegamer

david.ruegamer@gmail.com

Authors

Sarah Brockhaus

aut

David Ruegamer

aut / cre

Almond Stoecker

aut

Torsten Hothorn

ctb

with contributions by many others

ctb

(see inst/CONTRIBUTIONS)

Material

NEWS
Reference manual
Package source

In Views

FunctionalData

Vignettes

FDboost FLAM Canada
FDboost FLAM fuel
FDboost FLAM viscosity
FDboost density-on-scalar births

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

FDboost archive

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

Reverse Suggests

mlr