| as_nomogram | Construct nomogram ojects for high-dimensional Cox models | 
| calibrate | Calibrate high-dimensional Cox models | 
| calibrate_external | Externally calibrate high-dimensional Cox models | 
| compare_by_calibrate | Compare high-dimensional Cox models by model calibration | 
| compare_by_validate | Compare high-dimensional Cox models by model validation | 
| fit_aenet | Model selection for high-dimensional Cox models with adaptive elastic-net penalty | 
| 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 | 
| fit_flasso | Model selection for high-dimensional Cox models with fused lasso penalty | 
| fit_lasso | Model selection for high-dimensional Cox models with lasso penalty | 
| fit_mcp | Model selection for high-dimensional Cox models with MCP penalty | 
| fit_mnet | Model selection for high-dimensional Cox models with Mnet penalty | 
| fit_scad | Model selection for high-dimensional Cox models with SCAD penalty | 
| fit_snet | Model selection for high-dimensional Cox models with Snet penalty | 
| glmnet_basesurv | Breslow baseline hazard estimator for glmnet objects | 
| glmnet_survcurve | Survival curve prediction for glmnet objects | 
| 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 | 
| logrank_test | Log-rank test for internal calibration and external calibration results | 
| ncvreg_basesurv | Breslow baseline hazard estimator for ncvreg objects | 
| ncvreg_survcurve | Survival curve prediction for ncvreg objects | 
| penalized_basesurv | Breslow baseline hazard estimator for penfit objects | 
| penalized_survcurve | Survival curve prediction for penfit objects | 
| plot.hdnom.calibrate | Plot calibration results | 
| plot.hdnom.calibrate.external | Plot external calibration results | 
| plot.hdnom.compare.calibrate | Plot model comparison by calibration results | 
| plot.hdnom.compare.validate | Plot model comparison by validation results | 
| plot.hdnom.nomogram | Plot nomogram objects | 
| plot.hdnom.validate | Plot optimism-corrected time-dependent discrimination curves for validation | 
| plot.hdnom.validate.external | Plot time-dependent discrimination curves for external validation | 
| predict.hdnom.model | Make predictions from high-dimensional Cox models | 
| print.hdnom.calibrate | Print calibration results | 
| print.hdnom.calibrate.external | Print external calibration results | 
| print.hdnom.compare.calibrate | Print model comparison by calibration results | 
| print.hdnom.compare.validate | Print model comparison by validation results | 
| print.hdnom.model | Print high-dimensional Cox model objects | 
| print.hdnom.nomogram | Print nomograms objects | 
| print.hdnom.validate | Print validation results | 
| print.hdnom.validate.external | Print external validation results | 
| smart | Imputed SMART study data | 
| smarto | Original SMART study data | 
| summary.hdnom.calibrate | Summary of calibration results | 
| summary.hdnom.calibrate.external | Summary of external calibration results | 
| summary.hdnom.compare.calibrate | Summary of model comparison by calibration results | 
| summary.hdnom.compare.validate | Summary of model comparison by validation results | 
| summary.hdnom.validate | Summary of validation results | 
| summary.hdnom.validate.external | Summary of external validation results | 
| theme_hdnom | Plot theme (ggplot2) for hdnom | 
| validate | Validate high-dimensional Cox models with time-dependent AUC | 
| validate_external | Externally validate high-dimensional Cox models with time-dependent AUC |