stabplot is an R package designed to facilitate regularisation tuning and convergence monitoring in stability selection using Lasso. It provides two core functions, Regustab and Convstab, which help visualise stability in regularised models, supporting users in selecting appropriate regularisation parameters and assessing convergence.
Help functions are available through R by ?stabplot, ?Regustab, and ?Convstab.
The methodology is based on the paper:
"Stability-guided hyper-parameter tuning for stability selection" (2026) Nouraie, Mahdi, and Samuel Muller, Communications in Statistics-Theory and Methods.
You can install and load the stabplot package using the following commands
in R:
# Install the stabplot package from CRAN
install.packages("stabplot")
# Or install the stabplot package from GitHub
# Install 'devtools' if not already installed
if (!require("devtools")){install.packages("devtools")}
# devtools::install_github("MahdiNouraie/stabplot")
install.packages("stabplot", repos = c('https://mahdinouraie.r-universe.dev', 'https://cloud.r-project.org')) #installing stabplot
library(stabplot) #loading stabplot
Regustab function creates a plot that displays stability values in relation to regularisation values for Lasso through stability selection. The plot highlights key lambda values, including lambda.min, lambda.1se, and lambda.stable. If lambda.stable is not available, the function will display lambda.stable.1sd.
Regustab also returns a list containing the highlighted regularisation values — min, 1se, and stable (or stable.1sd) — accessible via res$min, res$`1se`, and res$stable.
A toy example of usage:
set.seed(123) # for reproducibility
x <- matrix(rnorm(1000), ncol = 10)
# create beta based on the first 3 columns of x and some error
beta <- c(1, 2, 3, rep(0, 7))
y <- x %*% beta + rnorm(100)
B <- 10 # number of sub-samples
res <- Regustab(x, y, B)
res
# $min
#[1] 0.07609021
#$`1se`
#[1] 0.2550241
#$stable
#[1] 0.3371269
Convstab creates a plot displaying stability values along with confidence intervals, against the sequential sub-sampling index within stability selection. This plot aids in monitoring the convergence status of stability values. The function uses lambda.stable to generate the plot; if lambda.stable is unavailable, it defaults to lambda.stable.1sd.
The function returns a list containing the plot (res$plot) and a data frame of variables whose selection frequencies exceed thr (res$selected), so both can be accessed or reused after the call.
A toy example of usage:
set.seed(123) # for reproducibility
x <- matrix(rnorm(1000), ncol = 10)
# create beta based on the first 3 columns of x and some error
beta <- c(0.5, 0.4, 0.3, rep(0, 7))
y <- x %*% beta + rnorm(100)
B <- 200 #number of sub-samples
alpha <- 0.05 #significance level of confidence interval
thr <- 0.5 # threshold for filtering variables based on their selection frequencies
res <- Convstab(x, y, B, alpha, thr)
res$selected
# Variable Selection_Frequency
#1 x1 0.970
#2 x2 0.895
