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Bayenet
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]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.Bayenet . Bayenet results . Bayenet.pdf . Bayenet_0.3.tar.gz . Bayenet_0.3.zip . Bayenet_0.3.zip . Bayenet_0.3.zip . Bayenet_0.3.tgz . Bayenet_0.3.tgz . Bayenet_0.3.tgz . Bayenet_0.3.tgz . Bayenet_0.3.tgz . Bayenet_0.3.tgz . Bayenet archive . https://CRAN.R-project.org/package=Bayenet .
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 29 Mar. 2025.
Other packages that cited Bayenet R package
View Bayenet citation profile
Other R packages that Bayenet depends,
imports, suggests or enhances
Complete documentation for Bayenet
Functions, R codes and Examples using
the Bayenet R package
Some associated functions: Bayenet-package . Bayenet . Selection . dat . predict.Bayenet . print.Bayenet . print.Bayenet.pred . print.Selection .
Some associated R codes: Bayenet-package.R . Bayenet.R . DataMatrix.R . Qenet.R . Qenetss.R . RcppExports.R . Selection.NonSparse.R . Selection.R . Selection.Sparse.R . data.R . enet.R . enetss.R . mpm.R . nonrobust.R . predict.Bayenet.R . print.Bayenet.R . quanfun.R . robust.R . Full Bayenet package functions and examples
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