Package: hdnom 6.2.0

hdnom: Benchmarking and Visualization Toolkit for Penalized Cox Models

Creates nomogram visualizations for penalized Cox regression models, with the support of reproducible survival model building, validation, calibration, and comparison for high-dimensional data.

Authors:Nan Xiao [aut, cre], Qing-Song Xu [aut], Miao-Zhu Li [aut], Frank Harrell [ctb], Sergej Potapov [ctb], Werner Adler [ctb], Matthias Schmid [ctb]

hdnom_6.2.0.tar.gz
hdnom_6.2.0.zip(r-4.7)hdnom_6.2.0.zip(r-4.6)hdnom_6.2.0.zip(r-4.5)
hdnom_6.2.0.tgz(r-4.6-x86_64)hdnom_6.2.0.tgz(r-4.6-arm64)hdnom_6.2.0.tgz(r-4.5-x86_64)hdnom_6.2.0.tgz(r-4.5-arm64)
hdnom_6.2.0.tar.gz(r-4.7-arm64)hdnom_6.2.0.tar.gz(r-4.7-x86_64)hdnom_6.2.0.tar.gz(r-4.6-arm64)hdnom_6.2.0.tar.gz(r-4.6-x86_64)
hdnom_6.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
hdnom/json (API)
NEWS

# Install 'hdnom' in R:
install.packages('hdnom', repos = c('https://nanxstats.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nanxstats/hdnom/issues

Pkgdown/docs site:https://nanx.me

Uses libs:
  • openblas– Optimized BLAS
Datasets:
  • smart - Imputed SMART study data
  • smarto - Original SMART study data

On CRAN:

Conda:

benchmarkhigh-dimensional-datalinear-regressionnomogram-visualizationpenalized-cox-modelssurvival-analysisopenblas

8.83 score 47 stars 3 packages 71 scripts 374 downloads 9 mentions 26 exports 31 dependencies

Last updated from:c21297cc37. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK182
linux-devel-x86_64OK201
source / vignettesOK221
linux-release-arm64OK171
linux-release-x86_64OK177
macos-release-arm64OK153
macos-release-x86_64OK309
macos-oldrel-arm64OK226
macos-oldrel-x86_64OK366
windows-develOK158
windows-releaseOK155
windows-oldrelOK171
wasm-releaseOK101

Exports:as_nomogramcalibratecalibrate_externalcompare_by_calibratecompare_by_validatefit_aenetfit_alassofit_enetfit_flassofit_lassofit_mcpfit_mnetfit_scadfit_snetglmnet_basesurvglmnet_survcurveinfer_variable_typekmplotlogrank_testncvreg_basesurvncvreg_survcurvepenalized_basesurvpenalized_survcurvetheme_hdnomvalidatevalidate_external

Dependencies:clicodetoolscpp11farverforeachggplot2glmnetgluegridExtragtableisobanditeratorslabelinglatticelifecycleMatrixncvregpenalizedR6RColorBrewerRcppRcppArmadilloRcppEigenrlangS7scalesshapesurvivalvctrsviridisLitewithr

An Introduction to hdnom

Rendered fromhdnom.Rmdusingknitr::rmarkdownon May 11 2026.

Last update: 2025-06-09
Started: 2015-08-25

Readme and manuals

Help Manual

Help pageTopics
Construct nomogram ojects for high-dimensional Cox modelsas_nomogram
Calibrate high-dimensional Cox modelscalibrate
Externally calibrate high-dimensional Cox modelscalibrate_external
Compare high-dimensional Cox models by model calibrationcompare_by_calibrate
Compare high-dimensional Cox models by model validationcompare_by_validate
Model selection for high-dimensional Cox models with adaptive elastic-net penaltyfit_aenet
Model selection for high-dimensional Cox models with adaptive lasso penaltyfit_alasso
Model selection for high-dimensional Cox models with elastic-net penaltyfit_enet
Model selection for high-dimensional Cox models with fused lasso penaltyfit_flasso
Model selection for high-dimensional Cox models with lasso penaltyfit_lasso
Model selection for high-dimensional Cox models with MCP penaltyfit_mcp
Model selection for high-dimensional Cox models with Mnet penaltyfit_mnet
Model selection for high-dimensional Cox models with SCAD penaltyfit_scad
Model selection for high-dimensional Cox models with Snet penaltyfit_snet
Breslow baseline hazard estimator for glmnet objectsglmnet_basesurv
Survival curve prediction for glmnet objectsglmnet_survcurve
Extract information of selected variables from high-dimensional Cox modelsinfer_variable_type
Kaplan-Meier plot with number at risk table for internal calibration and external calibration resultskmplot
Log-rank test for internal calibration and external calibration resultslogrank_test
Breslow baseline hazard estimator for ncvreg objectsncvreg_basesurv
Survival curve prediction for ncvreg objectsncvreg_survcurve
Breslow baseline hazard estimator for penfit objectspenalized_basesurv
Survival curve prediction for penfit objectspenalized_survcurve
Plot calibration resultsplot.hdnom.calibrate
Plot external calibration resultsplot.hdnom.calibrate.external
Plot model comparison by calibration resultsplot.hdnom.compare.calibrate
Plot model comparison by validation resultsplot.hdnom.compare.validate
Plot nomogram objectsplot.hdnom.nomogram
Plot optimism-corrected time-dependent discrimination curves for validationplot.hdnom.validate
Plot time-dependent discrimination curves for external validationplot.hdnom.validate.external
Make predictions from high-dimensional Cox modelspredict.hdnom.model
Print calibration resultsprint.hdnom.calibrate
Print external calibration resultsprint.hdnom.calibrate.external
Print model comparison by calibration resultsprint.hdnom.compare.calibrate
Print model comparison by validation resultsprint.hdnom.compare.validate
Print high-dimensional Cox model objectsprint.hdnom.model
Print nomograms objectsprint.hdnom.nomogram
Print validation resultsprint.hdnom.validate
Print external validation resultsprint.hdnom.validate.external
Imputed SMART study datasmart
Original SMART study datasmarto
Summary of calibration resultssummary.hdnom.calibrate
Summary of external calibration resultssummary.hdnom.calibrate.external
Summary of model comparison by calibration resultssummary.hdnom.compare.calibrate
Summary of model comparison by validation resultssummary.hdnom.compare.validate
Summary of validation resultssummary.hdnom.validate
Summary of external validation resultssummary.hdnom.validate.external
Plot theme (ggplot2) for hdnomtheme_hdnom
Validate high-dimensional Cox models with time-dependent AUCvalidate
Externally validate high-dimensional Cox models with time-dependent AUCvalidate_external