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BayesS5
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Download and install BayesS5 package within the R console
Install from CRAN:
install.packages("BayesS5")
Install from Github:
library("remotes")
install_github("cran/BayesS5")
Install by package version:
library("remotes")
install_version("BayesS5", "1.41")
Attach the package and use:
library("BayesS5")
Maintained by
Minsuk Shin
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-01-17
Latest Update: 2020-03-24
Description:
In p >> n settings, full posterior sampling using existing Markov chain Monte
Carlo (MCMC) algorithms is highly inefficient and often not feasible from a practical
perspective. To overcome this problem, we propose a scalable stochastic search algorithm that is called the Simplified Shotgun Stochastic Search (S5) and aimed at rapidly explore interesting regions of model space and finding the maximum a posteriori(MAP) model. Also, the S5 provides an approximation of posterior probability of each model (including the marginal inclusion probabilities). This algorithm is a part of an article titled "Scalable Bayesian Variable Selection Using Nonlocal Prior Densities in Ultrahigh-dimensional Settings" (2018) by Minsuk Shin, Anirban Bhattacharya, and Valen E. Johnson and "Nonlocal Functional Priors for Nonparametric Hypothesis Testing and High-dimensional Model Selection" (2020+) by Minsuk Shin and Anirban Bhattacharya.
How to cite:
Minsuk Shin (2017). BayesS5: Bayesian Variable Selection Using Simplified Shotgun Stochastic Search with Screening (S5). R package version 1.41, https://cran.r-project.org/web/packages/BayesS5
Previous versions and publish date:
Other packages that cited BayesS5 R package
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Other R packages that BayesS5 depends,
imports, suggests or enhances
Functions, R codes and Examples using
the BayesS5 R package
Some associated functions: Bernoulli_Uniform . S5 . S5_additive . S5_parallel . SSS . Uniform . hyper_par . ind_fun_NLfP . ind_fun_g . ind_fun_pemom . ind_fun_pimom . obj_fun_g . obj_fun_pemom . obj_fun_pimom . result . result_est_LS . result_est_MAP .
Some associated R codes: Bernoulli_Uniform.R . S5.R . S5_additive.R . S5_parallel.R . SSS.R . Uniform.R . hyper_par.R . ind_fun_NLfP.R . ind_fun_g.R . ind_fun_pemom.R . ind_fun_pimom.R . obj_fun_g.R . obj_fun_pemom.R . obj_fun_pimom.R . result.R . result_est_LS.R . result_est_MAP.R . Full BayesS5 package functions and examples
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