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hdnom

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

Installation

You can install hdnom from CRAN:

install.packages("hdnom")

Or try the development version on GitHub:

remotes::install_github("nanxstats/hdnom")

Browse the vignettes to get started.

Gallery

Nomogram

Kaplan-Meier plot with number at risk table

Model validation and calibration

Model comparison by validation or calibration

Shiny app

Contribute

To contribute to this project, please take a look at the Contributing Guidelines first. Please note that the hdnom project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

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Version

Install

install.packages('hdnom')

Monthly Downloads

414

Version

6.2.1

License

GPL (>= 3)

Issues

1

Pull Requests

0

Stars

47

Forks

11

Maintainer

Nan Xiao

Last Published

July 28th, 2026

Functions in hdnom (6.2.1)

fit_snet

Model selection for high-dimensional Cox models with Snet penalty
fit_scad

Model selection for high-dimensional Cox models with SCAD penalty
glmnet_calibrate_surv_prob_pred

Compute glmnet predicted survival probabilities for calibration
glmnet_survcurve

Survival curve prediction for glmnet objects
fit_mnet

Model selection for high-dimensional Cox models with Mnet penalty
glmnet_basesurv

Breslow baseline hazard estimator for glmnet objects
fit_mcp

Model selection for high-dimensional Cox models with MCP penalty
glmnet_calibrate_external_surv_prob_pred

Compute glmnet predicted survival probabilities for external calibration
kmplot_raw

Kaplan-Meier Plot with Number at Risk Table
logrank_test

Log-rank test for internal calibration and external calibration results
palette_npg

Color Palette for NPG Journals
infer_variable_type

Extract information of selected variables from high-dimensional Cox models
kmplot

Kaplan-Meier plot with number at risk table for internal calibration and external calibration results
palette_lancet

Color Palette for Lancet Journals
plot.hdnom.calibrate

Plot calibration results
penalized_validate_tauc

Compute validation measures for penfit model objects
hdnom-package

hdnom: Benchmarking and Visualization Toolkit for Penalized Cox Models
ncvreg_validate_external_tauc

Compute external validation measures for ncvreg model objects
ncvreg_validate_tauc

Compute validation measures for ncvreg model objects
penalized_basesurv

Breslow baseline hazard estimator for penfit objects
penalized_calibrate_external_surv_prob_pred

Compute penfit predicted survival probabilities for external calibration
ncvreg_calibrate_surv_prob_pred

Compute ncvreg predicted survival probabilities for calibration
glmnet_validate_tauc

Compute validation measures for glmnet objects
print.hdnom.compare.calibrate

Print model comparison by calibration results
print.hdnom.calibrate.external

Print external calibration results
palette_aaas

Color Palette for AAAS Journals
plot.hdnom.validate.external

Plot time-dependent discrimination curves for external validation
plot.hdnom.validate

Plot optimism-corrected time-dependent discrimination curves for validation
summary.hdnom.compare.validate

Summary of model comparison by validation results
summary.hdnom.calibrate.external

Summary of external calibration results
ncvreg_survcurve

Survival curve prediction for ncvreg objects
summary.hdnom.compare.calibrate

Summary of model comparison by calibration results
plot.hdnom.compare.validate

Plot model comparison by validation results
ncvreg_tune_gamma_alpha

Automatic Mnet/Snet gamma and alpha tuning function by k-fold cross-validation
penalized_calibrate_surv_prob_pred

Compute penfit predicted survival probabilities for calibration
penalized_survcurve

Survival curve prediction for penfit objects
plot.hdnom.nomogram

Plot nomogram objects
predict.hdnom.model

Make predictions from high-dimensional Cox models
summary.hdnom.validate.external

Summary of external validation results
print.hdnom.calibrate

Print calibration results
penalized_tune_lambda

Automatic lambda tuning function for fused lasso by k-fold cross-validation
penalized_validate_external_tauc

Compute external validation measures for penfit model objects
fit_flasso

Model selection for high-dimensional Cox models with fused lasso penalty
glmnet_tune_alpha

Automatic alpha tuning function by k-fold cross-validation
glmnet_validate_external_tauc

Compute external validation measures for glmnet objects
ncvreg_tune_gamma

Automatic MCP/SCAD gamma tuning function by k-fold cross-validation
print.hdnom.validate.external

Print external validation results
theme_hdnom

Plot theme (ggplot2) for hdnom
fit_lasso

Model selection for high-dimensional Cox models with lasso penalty
ncvreg_basesurv

Breslow baseline hazard estimator for ncvreg objects
palette_jco

Color Palette for Journal of Clinical Oncology (JCO)
smarto

Original SMART study data
summary.hdnom.calibrate

Summary of calibration results
validate_external

Externally validate high-dimensional Cox models with time-dependent AUC
smart

Imputed SMART study data
validate

Validate high-dimensional Cox models with time-dependent AUC
summary.hdnom.validate

Summary of validation results
plot.hdnom.compare.calibrate

Plot model comparison by calibration results
plot.hdnom.calibrate.external

Plot external calibration results
print.hdnom.compare.validate

Print model comparison by validation results
print.hdnom.model

Print high-dimensional Cox model objects
ncvreg_calibrate_external_surv_prob_pred

Compute ncvreg predicted survival probabilities for external calibration
print.hdnom.nomogram

Print nomograms objects
print.hdnom.validate

Print validation results
compare_by_validate

Compare high-dimensional Cox models by model validation
calibrate_surv_prob_true

Compute Kaplan-Meier estimated survival probabilities for calibration
calibrate_external

Externally calibrate high-dimensional Cox models
as_nomogram

Construct nomogram ojects for high-dimensional Cox models
calibrate

Calibrate high-dimensional Cox models
fit_aenet

Model selection for high-dimensional Cox models with adaptive elastic-net penalty
compare_by_calibrate

Compare high-dimensional Cox models by model calibration
calibrate_external_surv_prob_true

Compute Kaplan-Meier estimated survival probabilities for external calibration
fit_alasso

Model selection for high-dimensional Cox models with adaptive lasso penalty
fit_enet

Model selection for high-dimensional Cox models with elastic-net penalty