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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", "1.7.5") 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
10.32614/CRAN.package.BAS . https://github.com/merliseclyde/BAS/issues . https://merliseclyde.github.io/BAS/ . https://github.com/merliseclyde/BAS . BAS citation info . BAS results . BAS.pdf . Using the Bayesian Adaptive Sampling (BAS) Package for Bayesian Model Averaging and Variable Selection . BAS_1.7.5.tar.gz . BAS_1.7.5.zip . BAS_1.7.5.zip . BAS_1.7.5.zip . BAS_1.7.5.tgz . BAS_1.7.5.tgz . BAS_1.7.5.tgz . BAS_1.7.5.tgz . BAS_1.7.5.tgz . BAS_1.7.5.tgz . BAS archive . https://CRAN.R-project.org/package=BAS .
First Published: 2009-03-02
Latest Update: 2022-11-02
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 1.7.5, https://cran.r-project.org/web/packages/BAS. Accessed 06 Apr. 2025.
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)
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
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