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 |
| Reference manual: | HCPclust.html , HCPclust.pdf |
| 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 |
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