Welcome to ClientVPS Mirrors

CRAN: Package HCPclust

HCPclust: Hierarchical Conformal Prediction for Clustered Data with Missing Responses

Implements hierarchical conformal prediction for clustered data with missing responses. The method uses repeated cluster-level splitting and within-cluster subsampling to accommodate dependence, and inverse-probability weighting to correct distribution shift induced by missingness. Conditional densities are estimated by inverting fitted conditional quantiles (linear quantile regression or quantile regression forests), and p-values are aggregated across resampling and splitting steps using the Cauchy combination test.

Version: 0.1.1
Imports: stats, grf, quantreg, xgboost, quantregForest
Suggests: foreach, doParallel, doRNG, parallel, testthat (≥ 3.0.0), knitr, rmarkdown, FNN, rstudioapi
Published: 2026-01-30
DOI: 10.32614/CRAN.package.HCPclust
Author: Menghan Yi [aut, cre], Judy Wang [aut]
Maintainer: Menghan Yi <menghany at umich.edu>
BugReports: https://github.com/judywangstat/HCP/issues
License: MIT + file LICENSE
URL: https://github.com/judywangstat/HCP
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: HCPclust results

Documentation:

Reference manual: HCPclust.html , HCPclust.pdf

Downloads:

Package source: HCPclust_0.1.1.tar.gz
Windows binaries: r-devel: HCPclust_0.1.1.zip, r-release: HCPclust_0.1.1.zip, r-oldrel: HCPclust_0.1.1.zip
macOS binaries: r-release (arm64): HCPclust_0.1.1.tgz, r-oldrel (arm64): HCPclust_0.1.1.tgz, r-release (x86_64): HCPclust_0.1.1.tgz, r-oldrel (x86_64): HCPclust_0.1.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=HCPclust to link to this page.

Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.

This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.