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qris  

Quantile Regression Model for Residual Lifetime Using an Induced Smoothing Approach
View on CRAN: Click here


Download and install qris package within the R console
Install from CRAN:
install.packages("qris")

Install from Github:
library("remotes")
install_github("cran/qris")

Install by package version:
library("remotes")
install_version("qris", "1.1.1")



Attach the package and use:
library("qris")
Maintained by
Kyu Hyun Kim
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-08-29
Latest Update: 2024-03-05
Description:
A collection of functions is provided by this package to fit quantiles regression models for censored residual lifetimes. It provides various options for regression parameters estimation: the induced smoothing approach (smooth), and L1-minimization (non-smooth). It also implements the estimation methods for standard errors of the regression parameters estimates based on an efficient partial multiplier bootstrap method and robust sandwich estimator. Furthermore, a simultaneous procedure of estimating regression parameters and their standard errors via an iterative updating procedure is implemented (iterative). For more details, see Kim, K. H., Caplan, D. J., & Kang, S. (2022), "Smoothed quantile regression for censored residual life", Computational Statistics, 1-22 .
How to cite:
Kyu Hyun Kim (2022). qris: Quantile Regression Model for Residual Lifetime Using an Induced Smoothing Approach. R package version 1.1.1, https://cran.r-project.org/web/packages/qris. Accessed 25 Jun. 2026.
Previous versions and publish date:
1.0.0 (2022-08-29 11:20), 1.1.1 (2024-03-05 15:40)
Other packages that cited qris R package
View qris citation profile
Other R packages that qris depends, imports, suggests or enhances
Complete documentation for qris
Functions, R codes and Examples using the qris R package
Some associated functions: export_Surv . ghat . plot.qris . qris-package . qris.control . qris . 
Some associated R codes: RcppExports.R . Surv.R . plot.R . qris.R . qris_fit.R . qris_pkg.R . summary.R .  Full qris package functions and examples
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