devtools, forcats, knitr, lme4, rmarkdown, roxygen2,
testthat, mice

c(
person(c("Joshua", "M"), "Rosenberg", role = c("aut", "cre"), email = "jmichaelrosenberg@gmail.com"),
person(c("Ran"), "Xu", role = "ctb", email = "ranxu@msu.edu"),
person(c("Qinyun"), "Lin", role = "ctb", email = "linqinyun1001@gmail.com"),
person(c("Kenneth", "A"), "Frank", role = "ctb", email = "kenfrank@msu.edu")
)
broom, crayon, dplyr, ggplot2, mice, purrr, rlang, tidyr
margins, pbkrtest, devtools, forcats, knitr, lme4, rmarkdown,
roxygen2, testthat
Joshua M Rosenberg [aut, cre],
Ran Xu [ctb],
Qinyun Lin [ctb],
Kenneth A Frank [ctb]

c(
person(c("Joshua", "M"), "Rosenberg", role = c("aut", "cre"), email = "jmrosenberg@utk.edu"),
person(c("Ran"), "Xu", role = "aut", email = "ran.2.xu@uconn.edu"),
person(c("Qinyun"), "Lin", role = "aut", email = "linqinyun1001@gmail.com"),
person(c("Kenneth", "A"), "Frank", role = "aut", email = "kenfrank@msu.edu")
)
broom, broom.mixed, crayon, dplyr, ggplot2, mice, purrr,
rlang, tidyr
margins, pbkrtest, devtools, forcats, knitr, lme4, rmarkdown,
roxygen2, testthat, ggrepel
Joshua M Rosenberg [aut, cre],
Ran Xu [aut],
Qinyun Lin [aut],
Kenneth A Frank [aut]

c(
person(c("Joshua", "M"), "Rosenberg", role = c("aut", "cre"), email = "jmichaelrosenberg@gmail.com"),
person(c("Ran"), "Xu", role = "ctb", email = "ranxu@msu.edu"),
person(c("Qinyun"), "Lin", role = "ctb", email = "linqinyun1001@gmail.com"),
person(c("Spiro"), "Maroulis", role = "ctb", email = "Spiro.Maroulis@asu.edu"),
person(c("Kenneth", "A"), "Frank", role = "ctb", email = "kenfrank@msu.edu")
)
broom, broom.mixed, crayon, dplyr, ggplot2, mice, purrr,
rlang, tidyr, tibble
margins, pbkrtest, devtools, forcats, knitr, lme4, rmarkdown,
roxygen2, testthat, ggrepel, covr
Joshua M Rosenberg [aut, cre],
Ran Xu [ctb],
Qinyun Lin [ctb],
Spiro Maroulis [ctb],
Kenneth A Frank [ctb]

Variable Selection by Revisited Knockoffs Procedures
c(person("Clemence", "Karmann", email = "clemence.karmann@gmail.com", role = c("aut","cre")),person("Aurelie", "Gueudin", email = "aurelie.gueudin@univ-lorraine.fr", role = c("aut")))
Performs variable selection for many types of L1-regularised regressions using the revisited knockoffs procedure. This procedure uses a matrix of knockoffs of the covariates independent from the response variable Y. The idea is to determine if a covariate belongs to the model depending on whether it enters the model before or after its knockoff. The procedure suits for a wide range of regressions with various types of response variables. Regression models available are exported from the R packages 'glmnet' and 'ordinalNet'. Based on the paper linked to via the URL below: Gegout A., Gueudin A., Karmann C. (2019) <arXiv:1907.03153>.
Clemence Karmann [aut, cre],
Aurelie Gueudin [aut]