Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 92 tok/s
Gemini 2.5 Pro 49 tok/s Pro
GPT-5 Medium 32 tok/s
GPT-5 High 40 tok/s Pro
GPT-4o 83 tok/s
GPT OSS 120B 467 tok/s Pro
Kimi K2 197 tok/s Pro
2000 character limit reached

Boosting Functional Regression Models with FDboost (1705.10662v3)

Published 30 May 2017 in stat.CO

Abstract: 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.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.