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Bayenet  

Bayesian Quantile Elastic Net for Genetic Study
View on CRAN: Click here


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

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

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



Attach the package and use:
library("Bayenet")
Maintained by
Xi Lu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-05-24
Latest Update: 2023-05-24
Description:
As heavy-tailed error distribution and outliers in the response variable widely exist, models which are robust to data contamination are highly demanded. Here, we develop a novel robust Bayesian variable selection method with elastic net penalty for quantile regression in genetic analysis. In particular, the spike-and-slab priors have been incorporated to impose sparsity. An efficient Gibbs sampler has been developed to facilitate computation.The core modules of the package have been developed in 'C++' and R.
How to cite:
Xi Lu (2023). Bayenet: Bayesian Quantile Elastic Net for Genetic Study. R package version 0.2, https://cran.r-project.org/web/packages/Bayenet. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1 (2023-05-24 11:00)
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