R package citation, R package reverse dependencies, R package scholars, install an r package from GitHub hy is package acceptance pending why is package undeliverable amazon why is package on hold dhl tour packages why in r package r and r package full form why is r free why r is bad which r package to install which r package has which r package which r package version which r package readxl which r package ggplot which r package fread which r package license where is package.json where is package-lock.json where is package.swift where is package explorer in eclipse where is package where is package manager unity where is package installer android where is package manager console in visual studio who r package which r package to install which r package version who is package who is package deal who is package design r and r package full form r and r package meaning what r package has what package r what is package in java what is package what is package-lock.json what is package in python what is package.json what is package installer do r package can't install r packages r can't find package r can't load package can't load xlsx package r can't install psych package r can't install sf package r Write if else in NONMEM pk pd
BAS
Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling
View on CRAN: Click
here
Download and install BAS package within the R console
Install from CRAN:
install.packages("BAS")
Install from Github:
library("remotes")
install_github("cran/BAS") Install by package version:
library("remotes")
install_version("BAS", "2.0.2") Attach the package and use:
library("BAS")
Maintained by
Merlise Clyde
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2009-03-02
Latest Update: 2024-11-28
Description:
Package for Bayesian Variable Selection and Model Averaging
in linear models and generalized linear models using stochastic or
deterministic sampling without replacement from posterior
distributions. Prior distributions on coefficients are
from Zellner's g-prior or mixtures of g-priors
corresponding to the Zellner-Siow Cauchy Priors or the
mixture of g-priors from Liang et al (2008)
for linear models or mixtures of g-priors from Li and Clyde
(2019) in generalized linear models.
Other model selection criteria include AIC, BIC and Empirical Bayes
estimates of g. Sampling probabilities may be updated based on the sampled
models using sampling w/out replacement or an efficient MCMC algorithm which
samples models using a tree structure of the model space
as an efficient hash table. See Clyde, Ghosh and Littman (2010)
for details on the sampling algorithms.
Uniform priors over all models or beta-binomial prior distributions on
model size are allowed, and for large p truncated priors on the model
space may be used to enforce sampling models that are full rank.
The user may force variables to always be included in addition to imposing
constraints that higher order interactions are included only if their
parents are included in the model.
This material is based upon work supported by the National Science
Foundation under Division of Mathematical Sciences grant 1106891.
Any opinions, findings, and
conclusions or recommendations expressed in this material are those of
the author(s) and do not necessarily reflect the views of the
National Science Foundation.
How to cite:
Merlise Clyde (2009). BAS: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling. R package version 2.0.2, https://cran.r-project.org/web/packages/BAS. Accessed 05 Aug. 2026.
Previous versions and publish date:
0.1 (2009-03-02 10:05), 0.3 (2009-05-29 09:01), 0.4 (2009-12-28 21:01), 0.45 (2009-12-30 09:03), 0.80 (2010-04-06 10:57), 0.85 (2010-04-29 08:51), 0.90 (2010-07-24 21:40), 0.91 (2010-09-09 18:54), 0.92 (2010-10-01 10:22), 1.0.5 (2015-09-10 16:38), 1.0.6 (2015-10-28 00:34), 1.0.8 (2015-11-12 18:59), 1.0.9 (2016-02-03 22:53), 1.0 (2012-06-01 06:41), 1.1.0 (2016-03-31 17:38), 1.2.0 (2016-04-12 01:26), 1.2.1 (2016-04-16 04:27), 1.2.2 (2016-07-01 01:15), 1.3.0 (2016-07-16 09:46), 1.4.0 (2016-08-27 07:52), 1.4.1 (2016-09-20 06:44), 1.4.2 (2016-10-13 20:36), 1.4.3 (2017-02-21 08:02), 1.4.4 (2017-03-14 19:45), 1.4.5 (2017-03-31 08:12), 1.4.6 (2017-05-26 23:12), 1.4.7 (2017-10-22 19:48), 1.4.8 (2018-03-12 16:04), 1.4.9 (2018-03-25 13:27), 1.5.0 (2018-05-03 23:19), 1.5.1 (2018-06-07 15:51), 1.5.2 (2018-10-25 10:00), 1.5.3 (2018-10-30 11:40), 1.5.4 (2020-01-19 18:00), 1.5.5 (2020-01-24 23:50), 1.6.0 (2021-11-13 00:00), 1.6.2 (2022-04-26 09:30), 1.6.3 (2022-10-19 08:47), 1.6.4 (2022-11-02 11:33), 1.6.6 (2023-11-29 01:10), 1.7.1 (2023-12-06 11:40), 1.7.2 (2024-09-17 02:00), 1.7.3 (2024-09-18 00:50), 1.7.5 (2024-11-28 12:50), 2.0.0 (2025-12-16 07:11), (2026-07-09 07:57)
Other packages that cited BAS R package
View BAS citation profile
Other R packages that BAS depends,
imports, suggests or enhances
Complete documentation for BAS
Functions, R codes and Examples using
the BAS R package
Some associated functions: BAS . Bayes.outlier . Bernoulli.heredity . Bernoulli . CCH . EB.global . EB.local . Hald . IC.prior . Jeffreys . TG . bas.glm . bas.lm . bayesglm.fit . beta.binomial . beta.prime . bodyfat . climate . coef . confint.coef . confint.pred . cv.summary.bas . diagnostics . eplogprob.marg . eplogprob . fitted . force.heredity.bas . g.prior . hyper.g.n . hyper.g . hypergeometric1F1 . hypergeometric2F1 . image.bas . intrinsic . list2matrix . list2matrix.which . phi1 . plot.coef . plot.confint . plot . predict.bas . predict.basglm . print.bas . protein . robust . summary . tCCH . testBF.prior . tr.beta.binomial . tr.poisson . tr.power.prior . trCCH . uniform . update . variable.names.pred.bas . which.matrix .
Some associated R codes: BAS-package.R . EB_global.R . as_matrix.R . bas_glm.R . bas_lm.R . beta_priors.R . cch.R . coefficients.R . confint.R . cv_summary.R . data.R . diagnostics.R . eplogprob.R . glm_fit.R . gordy.R . hypergeometric1F1.R . hypergeometric2F1.R . image.R . interactions.R . model_priors.R . outliers.R . plot.R . plot_coef.R . predict.R . summary.R . update.R . Full BAS package functions and examples
Downloads during the last 30 days
Today's Hot Picks in Authors and Packages
kernelPSI
Post-Selection Inference for Nonlinear Variable Selection
Different post-selection inference strategies for kernelselection as described in kernelPSI a Post-S ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Lotfi Slim (view profile)
quickcode
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Obinna Obianom (view profile)
noisyr
Noise Quantification in High Throughput Sequencing Output
Quantifies and removes technical noise from high-throughput
sequencing data. Two approaches are use ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Ilias Moutsopoulos (view profile)
dcov
A Fast Implementation of Distance Covariance
Efficient methods for computing distance covariance and relevant statistics. See Sz ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Hang Weiqiang (view profile)
dhReg
Dynamic Harmonic Regression
Building and forecasting time series data with multiple seasonality using Dynamic Harmonic Regressio ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Pranay Gaikwad (view profile)
28,083
R Packages
239,283
Dependencies
74,457
Author Associations
28,084
Publication Badges
