This package is considered a duplicate. The official version of this package is found at:https://nilotpalsanyal.r-universe.dev/S3VS

Package: S3VS 1.1

Nilotpal Sanyal

S3VS: Structured Screen-and-Select Variable Selection in Linear, Generalized Linear, and Survival Models

Performs variable selection using the structured screen-and-select (S3VS) framework in linear models, generalized linear models with binary data, and survival models such as the Cox model and accelerated failure time (AFT) model.

Authors:Nilotpal Sanyal [aut, cre], Padmore N. Prempeh [aut]

S3VS_1.1.tar.gz
S3VS_1.1.zip(r-4.7-any)S3VS_1.1.zip(r-4.6-any)
S3VS_1.1.tar.gz(r-4.7-any)S3VS_1.1.tar.gz(r-4.6-any)
S3VS_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
S3VS/json (API)

# Install 'S3VS' in R:

install.packages('S3VS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nilotpalsanyal/s3vs/issues

Pkgdown/docs site:https://nilotpalsanyal.github.io

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC
c++– GNU Standard C++ Library v3

On CRAN:

jags cpp

3.00 score 468 downloads 24 exports 146 dependencies

Last updated from:fbafce606d. Checks:4 WARNING, 2 OK. Indexed: no.

Target	Result	Time
linux-devel	WARNING	192
source / vignettes	OK	243
linux-release	WARNING	185
windows-devel	WARNING	149
windows-release	WARNING	151
wasm-release	OK	154

Exports:bridge_aft get_leadsets get_leadvars get_leadvars_GLM get_leadvars_LM get_leadvars_SURV looprun pred_S3VS pred_S3VS_GLM pred_S3VS_LM pred_S3VS_SURV remove_vars S3VS S3VS_GLM S3VS_LM S3VS_SURV select_vars update_y update_y_GLM update_y_LM VS_method VS_method_GLM VS_method_LM VS_method_SURV

Dependencies:abind aftgee afthd backports base64enc BB bbmle bdsmatrix bitops boot broom bslib cachem caTools checkmate cli cluster cmprsk coda codetools colorspace cpp11 data.table diagram digest doParallel dplyr eha evaluate farver fastGHQuad fastmap fontawesome foreach foreign Formula fs future future.apply geepack generics ggplot2 glmnet globals glue gridExtra gtable highr Hmisc htmlTable htmltools htmlwidgets intervals isoband iterators jquerylib jsonlite KernSmooth knitr L0Learn labeling lattice lava lifecycle listenv lsoda lubridate magrittr MASS Matrix MatrixGenerics MatrixModels matrixStats mclust memoise mets mgcv mime modelSelection multcomp mvtnorm ncvreg nlme nnet numDeriv parallelly pec photobiology pillar pkgconfig plotrix plyr polspline polynom pracma prodlim progressr Publish purrr quadprog quantreg R2jags R2WinBUGS R6 ranger rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen reshape2 riskRegression rjags rlang rmarkdown rms rpart rstpm2 rstudioapi S7 sandwich sass scales shape SparseM sparseMatrixStats splus2R SQUAREM stringi stringr SunCalcMeeus survival TH.data tibble tidyr tidyselect timechange timereg tinytex utf8 vctrs viridisLite withr xfun yaml zoo

S3VS User Guide

Rendered fromS3VS_vignette.Rmdusingknitr::rmarkdown

Last update: 2026-09-07
Started: 2026-01-13

Citation

Readme and manuals

Help Manual

Help page	Topics
Structured Screen-and-Select Variable Selection in Linear, Generalized Linear, and Survival Models	S3VS-package
Bridge-Penalized AFT Regression via Iteratively Reweighted LASSO	bridge_aft
Identify Leading Sets of Covariates via Inter-Predictor Associations	get_leadsets
Screening Predictors As 'Leading Variables' By Evaluating Predictor-Response Associations	get_leadvars
Screening Predictors As 'Leading Variables' By Evaluating Predictor-Response Associations In Generalized Linear Models	get_leadvars_GLM
Screening Predictors As 'Leading Variables' By Evaluating Predictor-Response Associations In Linear Models	get_leadvars_LM
Screening Predictors As "Leading Variables" By Evaluating Predictor-Response Associations In Survival Models	get_leadvars_SURV
Decide Whether to Run Another S3VS Iteration	looprun
Prediction Using S3VS-Selected Predictors	pred_S3VS
Prediction Using S3VS-Selected Predictors in Survival Models	pred_S3VS_GLM
Prediction Using S3VS-Selected Predictors in Linear Models	pred_S3VS_LM
Predicted Survival Probabilities Using S3VS-Selected Predictors in Generalized Linear Models	pred_S3VS_SURV
Aggregate Not-Selected Predictors for Removal Across Multiple Leading Sets	remove_vars
Structured Screen-and-Select Variable Selection in Linear, Generalized Linear, and Survival Models	S3VS
Structured Screen-and-Select Variable Selection in Generalized Linear Models	S3VS_GLM
Structured Screen-and-Select Variable Selection in Linear Models	S3VS_LM
Structured Screen-and-Select Variable Selection in Survival Models	S3VS_SURV
Aggregate Selected Predictors Across Multiple Leading Sets	select_vars
Update Response Accounting for Selected Predictors	update_y
Update Response Accounting for Selected Predictors in Generalized Linear Models	update_y_GLM
Update Response Accounting for Selected Predictors in Linear Models	update_y_LM
Variable Selection in Leading Sets under the S3VS Framework	VS_method
Variable Selection in Leading Sets for Generalized Linear Models under the S3VS Framework	VS_method_GLM
Variable Selection in Leading Sets for Linear Models under the S3VS Framework	VS_method_LM
Variable Selection in Leading Sets for Survival Models under the S3VS Framework	VS_method_SURV

Package: S3VS 1.1

S3VS: Structured Screen-and-Select Variable Selection in Linear, Generalized Linear, and Survival Models

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)