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BVSNLP  

Bayesian Variable Selection in High Dimensional Settings using Nonlocal Priors
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BVSNLP", "1.1.9")



Attach the package and use:
library("BVSNLP")
Maintained by
Amir Nikooienejad
[Scholar Profile | Author Map]
First Published: 2017-12-18
Latest Update: 2020-08-28
Description:
Variable/Feature selection in high or ultra-high dimensional settings has gained a lot of attention recently specially in cancer genomic studies. This package provides a Bayesian approach to tackle this problem, where it exploits mixture of point masses at zero and nonlocal priors to improve the performance of variable selection and coefficient estimation. product moment (pMOM) and product inverse moment (piMOM) nonlocal priors are implemented and can be used for the analyses. This package performs variable selection for binary response and survival time response datasets which are widely used in biostatistic and bioinformatics community. Benefiting from parallel computing ability, it reports necessary outcomes of Bayesian variable selection such as Highest Posterior Probability Model (HPPM), Median Probability Model (MPM) and posterior inclusion probability for each of the covariates in the model. The option to use Bayesian Model Averaging (BMA) is also part of this package that can be exploited for predictive power measurements in real datasets.
How to cite:
Amir Nikooienejad (2017). BVSNLP: Bayesian Variable Selection in High Dimensional Settings using Nonlocal Priors. R package version 1.1.9, https://cran.r-project.org/web/packages/BVSNLP. Accessed 03 Apr. 2025.
Previous versions and publish date:
0.9.5 (2017-12-18 13:12), 0.9.6 (2017-12-19 21:23), 0.9.7 (2018-01-08 15:52), 0.9.8 (2018-01-13 01:23), 0.9.10 (2018-02-07 21:43), 1.1.0 (2018-03-27 01:10), 1.1.5 (2018-05-17 09:07), 1.1.8 (2019-06-12 07:40)
Other packages that cited BVSNLP R package
View BVSNLP citation profile
Other R packages that BVSNLP depends, imports, suggests or enhances
Complete documentation for BVSNLP
Functions, R codes and Examples using the BVSNLP R package
Some associated functions: CoefEst . HyperSelect . ModProb . PreProcess . bvs . cox_bvs . logreg_bvs . predBMA . 
Some associated R codes: CoefEst.R . HyperSelect.R . ModProb.R . PreProcess.R . RcppExports.R . bvs.R . matprep.R . predBMA.R . predmat.R . zzz.R .  Full BVSNLP package functions and examples
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