Package: qris 1.1.1
qris: Quantile Regression Model for Residual Lifetime Using an Induced Smoothing Approach
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 <doi:10.1007/s00180-022-01262-z>.
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qris_1.1.1.tar.gz
qris_1.1.1.tar.gz(r-4.5-noble)qris_1.1.1.tar.gz(r-4.4-noble)
qris_1.1.1.tgz(r-4.4-emscripten)qris_1.1.1.tgz(r-4.3-emscripten)
qris.pdf |qris.html✨
qris/json (API)
NEWS
# Install 'qris' in R: |
install.packages('qris', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kyuhyun07/qris/issues
Last updated 9 months agofrom:dfb00a4765. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 01 2024 |
R-4.5-linux-x86_64 | NOTE | Dec 01 2024 |
Exports:qrisqris.controlqris.extendSurv
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmgcvmunsellnleqslvnlmepillarpkgconfigquantregR6RColorBrewerRcppRcppArmadillorlangscalesSparseMstringistringrsurvivaltibbleutf8vctrsviridisLitewithr