Boosting Functional Regression Models with FDboost
Dublin Core
Title
Boosting Functional Regression Models with FDboost
Subject
: functional data analysis, function-on-function regression, function-on-scalar regression, gradient boosting, model-based boosting, scalar-on-function regression.
Description
The R add-on package FDboost is a flexible toolbox for the estimation of functional
regression models by model-based boosting. It provides the possibility to fit regression
models for scalar and functional response with effects of scalar as well as functional covariates, i.e., scalar-on-function, function-on-scalar and function-on-function regression
models. In addition to mean regression, quantile regression models as well as generalized
additive models for location scale and shape can be fitted with FDboost. Furthermore,
boosting can be used in high-dimensional data settings with more covariates than observations. We provide a hands-on tutorial on model fitting and tuning, including the
visualization of results. The methods for scalar-on-function regression are illustrated
with spectrometric data of fossil fuels and those for functional response regression with a
data set including bioelectrical signals for emotional episodes
regression models by model-based boosting. It provides the possibility to fit regression
models for scalar and functional response with effects of scalar as well as functional covariates, i.e., scalar-on-function, function-on-scalar and function-on-function regression
models. In addition to mean regression, quantile regression models as well as generalized
additive models for location scale and shape can be fitted with FDboost. Furthermore,
boosting can be used in high-dimensional data settings with more covariates than observations. We provide a hands-on tutorial on model fitting and tuning, including the
visualization of results. The methods for scalar-on-function regression are illustrated
with spectrometric data of fossil fuels and those for functional response regression with a
data set including bioelectrical signals for emotional episodes
Creator
Sarah Brockhaus
Source
https://www.jstatsoft.org/article/view/v094i10
Publisher
Ludwig-MaximilansUniversität München
Date
June 2020
Contributor
Fajar bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Sarah Brockhaus, “Boosting Functional Regression Models with FDboost,” Repository Horizon University Indonesia, accessed May 14, 2025, https://repository.horizon.ac.id/items/show/8143.