mboost: Model-Based Boosting

Canonical link: https://rscholar.com/pkg/mboost

Torsten Hothorn • Peter Buehlmann • Thomas Kneib • Matthias Schmid • Benjamin Hofner • Fabian Otto-Sobotka • Fabian Scheipl • Andreas Mayr • View description and downloads View dependencies GitHub project

2006 Published

2.9-11 Version

0 Citations

8 Authors

Referenced by ⇅	Year
CompareCausalNetworks: Interface to Diverse Estimation Methods of Causal Networks (Version 0.2.6.2)	2015
DIFboost: Detection of Differential Item Functioning (DIF) in Rasch Models by Boosting Techniques (Version 0.3)	2015
FDboost: Boosting Functional Regression Models (Version 1.1-2)	2014
GeDS: Geometrically Designed Spline Regression (Version 0.2.4)	2017
HSAUR2: A Handbook of Statistical Analyses Using R (2nd Edition) (Version 1.1-20)	2009
HSAUR3: A Handbook of Statistical Analyses Using R (3rd Edition) (Version 1.0-15)	2014
InvariantCausalPrediction: Invariant Causal Prediction (Version 0.8)	2014
MachineShop: Machine Learning Models and Tools (Version 3.8.0)	2018
RobustPrediction: Robust Tuning and Training for Cross-Source Prediction (Version 0.1.4)	0
biospear: Biomarker Selection in Penalized Regression Models (Version 1.0.2)	2017
boostrq: Boosting Regression Quantiles (Version 1.0.0)	2024
bujar: Buckley-James Regression for Survival Data with High-Dimensional Covariates (Version 0.2-11)	2014
carSurv: Correlation-Adjusted Regression Survival (CARS) Scores (Version 1.0.0)	2018
catdata: Categorical Data (Version 1.2.4)	2012
censored: 'parsnip' Engines for Survival Models (Version 0.3.2)	2022
expectreg: Expectile and Quantile Regression (Version 0.53)	2010
familiar: End-to-End Automated Machine Learning and Model Evaluation (Version 1.5.0)	2022
fastml: Fast Machine Learning Model Training and Evaluation (Version 0.1.0)	0
flowml: A Backend for a 'nextflow' Pipeline that Performs Machine-Learning-Based Modeling of Biomedical Data (Version 0.1.3)	2023
fscaret: Automated Feature Selection from 'caret' (Version 0.9.4.4)	2013
gamboostLSS: Boosting Methods for 'GAMLSS' (Version 2.0-7)	2011
gamboostMSM: Boosting Multistate Models (Version 1.1.88)	2014
geoGAM: Select Sparse Geoadditive Models for Spatial Prediction (Version 0.1-3)	2016
gfboost: Gradient-Free Gradient Boosting (Version 0.1.1)	2020
imputeR: A General Multivariate Imputation Framework (Version 2.2)	2014
mgwrsar: GWR and MGWR with Spatial Autocorrelation (Version 1.0.5)	2018
mlr: Machine Learning in R (Version 2.19.2)	2013
pre: Prediction Rule Ensembles (Version 1.0.7)	2016
sgboost: Sparse-Group Boosting (Version 0.1.3)	2024
spikeSlabGAM: Bayesian Variable Selection and Model Choice for Generalized Additive Mixed Models (Version 1.1-20)	2011
sqlscore: Utilities for Generating SQL Queries from Model Objects (Version 0.1.4)	2016
stabs: Stability Selection with Error Control (Version 0.6-4)	2014
survML: Tools for Flexible Survival Analysis Using Machine Learning (Version 1.2.0)	2023
survex: Explainable Machine Learning in Survival Analysis (Version 1.2.0)	2022
tbm: Transformation Boosting Machines (Version 0.3-6)	2019
tidyfit: Regularized Linear Modeling with Tidy Data (Version 0.7.2)	2022
visaOTR: Valid Improved Sparsity A-Learning for Optimal Treatment Decision (Version 0.1.0)	2022

RPKG Scholar presents a tabulation of an author's contribution in the development of R packages stored in the Comprehensive R Archive Network (CRAN). Within this site, we consider package dependencies (suggests,imports,depends,enhances) as citations because we believe that using one's package to develop another is tantamount to citing the author of the package being imported, suggested or enhanced.