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quasar is an R package that provides valid inference
procedures when multiple quantile regressions are fitted
simultaneously.
It implements the rank-score–based closed testing
approach proposed in:
De Santis, F., Vesely, A., and Andreella, A. (2025)
Inference on Multiple Quantiles in Regression Models by a Rank-Score Approach.
To install the development version from GitHub:
# install.packages("remotes")
remotes::install_github("angeella/quasar")library(quasar)
library(quantreg)
# Set the dimension of the covariates
p <- 3
Sigma <- diag(p)
# Simulate data
dat_n <- simulateData(
n = 200,
beta = 0,
gamma = c(0.2, -0.1),
mu = 4,
Sigma = Sigma,
sigma.y = 0.5,
distribution = "t"
)
# Fit quantile regressions
mod <- rq(
y ~ X + Z1 + Z2,
tau = c(0.1, 0.25, 0.5, 0.75, 0.9),
data = dat_n
)
# Perform closed testing based on rank-score statistics
closedTesting(mod, X = "X")The R scripts used to reproduce the simulation studies
(Figures 2 and 3 in the paper)
are available in the simulations/
folder of this repository.
Did you find some bugs?
Please write to angela.andreella[at]unive[dot]it
or open an issue on the GitHub Issues
page,
preferably including a reproducible example created with the reprex
package.
GPL (≥ 3)
If you use quasar in your research, please cite:
De Santis, F., Vesely, A., and Andreella, A. (2025).
Inference on Multiple Quantiles in Regression Models by a Rank-Score Approach.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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