R package BMA: Bayesian Model Averaging. Package for Bayesian model averaging for linear models, generalizable linear models and survival models (cox regression).
Keywords for this software
References in zbMATH (referenced in 11 articles , 1 standard article )
Showing results 1 to 11 of 11.
- Schomaker, Michael; Heumann, Christian: When and when not to use optimal model averaging (2020)
- Leopoldo Catania; Nima Nonejad: Dynamic Model Averaging for Practitioners in Economics and Finance: The eDMA Package (2018) not zbMATH
- Luca Scrucca; Adrian Raftery: clustvarsel: A Package Implementing Variable Selection for Gaussian Model-Based Clustering in R (2018) not zbMATH
- Xu, Jing; Tong, Xing-wei; Wang, Fang; Chen, Jian-ping: Learning dynamic causal relationships among sugar prices (2017)
- Vincenzo Lagani, Giorgos Athineou, Alessio Farcomeni, Michail Tsagris, Ioannis Tsamardinos: Feature Selection with the R Package MXM: Discovering Statistically-Equivalent Feature Subsets (2016) arXiv
- Fraley, Chris; Percival, Daniel: Model-averaged (\ell_1) regularization using Markov chain Monte Carlo model composition (2015)
- Marcin Błażejowski; Jacek Kwiatkowski: Bayesian Model Averaging and Jointness Measures for gretl (2015) not zbMATH
- Schomaker, Michael; Heumann, Christian: Model selection and model averaging after multiple imputation (2014)
- Liu, Juxin; Gustafson, Paul: On the detectability of different forms of interaction in regression models (2012)
- De Giuli, Maria Elena; Maggi, Mario Alessandro; Tarantola, Claudia: Bayesian outlier detection in capital asset pricing model (2010)
- Buchholz, Anika; Holländer, Norbert; Sauerbrei, Willi: On properties of predictors derived with a two-step bootstrap model averaging approach-A simulation study in the linear regression model (2008)