Other packages > Find by keyword >

MEGB  

Gradient Boosting for Longitudinal Data
View on CRAN: Click here


Download and install MEGB package within the R console
Install from CRAN:
install.packages("MEGB")

Install from Github:
library("remotes")
install_github("cran/MEGB")

Install by package version:
library("remotes")
install_version("MEGB", "0.2")



Attach the package and use:
library("MEGB")
Maintained by
Oyebayo Ridwan Olaniran
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-01-29
Latest Update: 2025-01-29
Description:
Gradient boosting is a powerful statistical learning method known for its ability to model complex relationships between predictors and outcomes while performing inherent variable selection. However, traditional gradient boosting methods lack flexibility in handling longitudinal data where within-subject correlations play a critical role. In this package, we propose a novel approach Mixed Effect Gradient Boosting ('MEGB'), designed specifically for high-dimensional longitudinal data. 'MEGB' incorporates a flexible semi-parametric model that embeds random effects within the gradient boosting framework, allowing it to account for within-individual covariance over time. Additionally, the method efficiently handles scenarios where the number of predictors greatly exceeds the number of observations (p>>n) making it particularly suitable for genomics data and other large-scale biomedical studies.
How to cite:
Oyebayo Ridwan Olaniran (2025). MEGB: Gradient Boosting for Longitudinal Data. R package version 0.2, https://cran.r-project.org/web/packages/MEGB. Accessed 13 Sep. 2026.
Previous versions and publish date:
0.1 (2025-01-29 18:00), (2026-07-09 08:09)
Other packages that cited MEGB R package
View MEGB citation profile
Other R packages that MEGB depends, imports, suggests or enhances
Complete documentation for MEGB
Functions, R codes and Examples using the MEGB R package
Full MEGB package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

saeMSPE  
Computing MSPE Estimates in Small Area Estimation
We describe a new R package entitled 'saeMSPE' for the well-known Fay Herriot model and nested error ...
Download / Learn more Package Citations See dependency  
oii  
Crosstab and Statistical Tests for OII MSc Stats Course
Provides simple crosstab output with optional statistics (e.g., Goodman-Kruskal Gamma, Somers' d, an ...
Download / Learn more Package Citations See dependency  
cmdfun  
Framework for Building Interfaces to Shell Commands
Writing interfaces to command line software is cumbersome. 'cmdfun' provides a framework for buildi ...
Download / Learn more Package Citations See dependency  
TSEwgt  
Total Survey Error Under Multiple, Different Weighting Schemes
Calculates total survey error (TSE) for a survey under multiple, different weighting schemes, using ...
Download / Learn more Package Citations See dependency  
tvmComp  
Discounting and Compounding Calculations for Various Scenarios
Functions for compounding and discounting calculations included here serve as a complete reference f ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  

28,565

R Packages

239,283

Dependencies

75,677

Author Associations

28,481

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA