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qris (version 1.1.1)

Quantile Regression Model for Residual Lifetime Using an Induced Smoothing Approach

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 .

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install.packages('qris')

Monthly Downloads

48

Version

1.1.1

License

GPL (>= 3)

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Maintainer

Kyu Hyun Kim

Last Published

March 5th, 2024

Functions in qris (1.1.1)

qris.extend

Extend a "qris" object to a specified range of \(tau\) or \(t_0\) values.
qris

Estimate a quantile regression estimator of residual lifetime from survival data
qris.control

Auxiliary for Controlling qris
predict.qris

Prediction for Quantile Regression Model Fitted on Residual life
qris-package

qris: Quantile Regression Model for Residual Lifetime Using an Induced Smoothing Approach
export_Surv

Surv function imported from survival
plot.qris

Draw 95% confidence interval by a quantile regression estimator of residual lifetime from survival data
residuals.qris

Residuals for Quantile Regression Model Fitted on Residual life