Package: SSVS
Title: Functions for Stochastic Search Variable Selection (SSVS)
Version: 1.0.0
Authors@R: c(person(given="Sierra",
         family="Bainter",
         role=c("cre", "aut"),
         email="sbainter@miami.edu"),
  person(given="Thomas",
         family="McCauley",
         role=c("aut"),
         email="thomasgranvillemccauley@gmail.com"),
  person(given="Mahmoud",
         family="Fahmy",
         role=c("aut"),
         email="mahmoud.m.fahm@gmail.com"),
  person("Dean", "Attali", 
         role = "aut",
         email = "daattali@gmail.com", 
         comment= c(ORCID="0000-0002-5645-3493")))
Description: Functions for performing stochastic search variable selection (SSVS) 
    for binary and continuous outcomes and visualizing the results. 
    SSVS is a Bayesian variable selection method used to estimate the probability 
    that individual predictors should be included in a regression model. 
    Using MCMC estimation, the method samples thousands of regression models 
    in order to characterize the model uncertainty regarding both the predictor 
    set and the regression parameters. 
URL: https://github.com/sabainter/SSVS
BugReports: https://github.com/sabainter/SSVS/issues
Depends: R (>= 2.10)
Imports: bayestestR, BoomSpikeSlab, checkmate, ggplot2, graphics,
        rlang, stats
Suggests: AER, testthat (>= 3.0.0), knitr, rmarkdown
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.2
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2022-03-03 17:28:57 UTC; Dean-X1C
Author: Sierra Bainter [cre, aut],
  Thomas McCauley [aut],
  Mahmoud Fahmy [aut],
  Dean Attali [aut] (<https://orcid.org/0000-0002-5645-3493>)
Maintainer: Sierra Bainter <sbainter@miami.edu>
Repository: CRAN
Date/Publication: 2022-03-08 20:20:12 UTC
Built: R 4.0.5; ; 2022-04-21 10:46:35 UTC; windows
