What varPro is | Regression: Boston housing | Per-tree importance with gg_varpro() | Partial dependence with gg_partial_varpro() | Per-rule lasso refinement with gg_beta_varpro() | Unsupervised views: see the uvarpro vignette | Anomaly scoring with gg_isopro() | Local importance with gg_ivarpro() | Classification: iris | Class-conditional importance with gg_varpro(conditional = TRUE) | Partial dependence: gg_partial_varpro() on classification | Per-class lasso refinement with gg_beta_varpro() | Survival: PBC | Variable importance: gg_varpro() | Partial dependence: gg_partial_varpro() on survival | Anomaly scoring: gg_isopro() on the X-matrix | Not available for survival: gg_beta_varpro, gg_ivarpro | Cross-cutting reference | Family-support matrix | Which variables can you actually get? | Factor-level ordering | Caching the expensive calls | Provenance shape | Further reading | References

Work in progress | Introduction | Data: Iris Flower Measurements | Exploratory data analysis | Growing a Random Forest | OOB error convergence | OOB predictions | Variable Selection | Variable importance (VIMP) | Minimal depth | SHAP Analysis | SHAP importance | SHAP beeswarm | SHAP dependence | Variable Dependence | Variable dependence plots | Partial dependence | Classification Performance: ROC and AUC | Conclusion | References

Work in progress | Introduction | Data: Boston Housing Values | Exploratory data analysis | Growing a Random Forest | OOB error convergence | OOB predictions | Variable Selection | Variable importance (VIMP) | Minimal depth | SHAP Analysis | SHAP importance | SHAP beeswarm | SHAP dependence | Variable Dependence | Variable dependence plots | Partial dependence | Variable Interactions and Conditioning Plots | Conditioning on a categorical variable | Conditioning on a continuous variable | Partial Dependence Surface | Conclusion | References

Work in progress | Introduction | Data: Primary Biliary Cirrhosis (PBC) | Data cleaning | Exploratory data analysis | Kaplan--Meier survival by treatment | Growing a Random Survival Forest | OOB error convergence | OOB predicted survival | Test set predictions | Variable Selection | Variable importance (VIMP) | Minimal depth | Variable Dependence | Variable dependence plots | Partial dependence | Conditional dependence | Partial Dependence Surfaces | Brier Score and CRPS | Conclusion | References

Importance without a response | One fit, three views | What depends on what: gg_udependent() | What ranks highest: gg_beta_uvarpro() | Where to draw the line: gg_sdependent() | Reading the three together | References

Error trajectories with gg_error() | Marginal dependence via gg_variable() | Variable importance with gg_vimp() | Balanced conditioning cuts with quantile_pts() | Next steps

Intercept-only model: CABG survival (KU Leuven) | Multivariable model: AVC repair | Multiphase model: additive hazard decomposition | Multi-endpoint models: heart valve replacement | Interval and left censoring | Status codes | Mixed censoring example | Interval-censored vs naive right-censored | Convergence troubleshooting | Reading the KM cumulative hazard for starting values | When to fix shape parameters | Signs of overparameterization | Optimizer options | Phase types reference

Exploratory covariate screening | Quantile calibration with hzr_calibrate() | Nonparametric baselines | Bootstrap confidence intervals | Goodness-of-fit overlay | Decile-of-risk calibration | Sensitivity analysis | Analysis workflow summary

Generalized Temporal Decomposition | The parametric family | SAS/C parameter bridge | The six valid cases | Derivation sketch | Additive Multiphase Hazard Model | Model specification | SAS/C bridge | Derived quantities | Constructing phases in R | Additive composition example | Maximum Likelihood Estimation | Log-likelihood under mixed censoring | Internal parameterization | Optimization strategy | Covariates and Phase-Specific Formulas | Global covariates | Phase-specific covariates | Time-varying coefficients | Multiphase vs. time-varying coefficients | Identifiability and Practical Considerations | Parameter identifiability | Numerical stability | Summary of Key Functions | References

Data preparation | Step 1: Nonparametric baseline | Step 2: Shape fitting --- simple to complex | 2a. Single-phase Weibull | 2b. Two-phase model (early CDF + constant) | 2c. Decomposed hazard | Step 3: Variable screening | 3a. Univariable logistic screening | 3b. Functional form assessment | Step 4: Multivariable model | 4a. Manual specification | 4b. Automated stepwise selection | Step 5: Prediction | 5a. Baseline survival curve | 5b. Sensitivity analysis --- risk factor comparison | Step 6: Validation --- decile-of-risk calibration | Conservation of events check | Why not Cox regression? | Summary

A first Weibull fit | Prediction workflow | Visualizing predicted survival | Multiphase models | Why multiple phases? | Decomposed hazard visualization | Multiphase survival with Kaplan-Meier overlay | Phase types | Numerical helpers

Overview | Statement-by-statement mapping | PROC HAZARD DATA= | TIME | EVENT | PARMS | EARLY and CONSTANT covariate blocks | SELECTION | SAS macro equivalents | Full worked example: AVC death after repair | SAS (original) | R equivalent (current runnable translation pattern) | Data preparation differences | Output object | Prediction | Known limitations vs. SAS HAZARD | Stepwise variable selection (SELECTION statement) | Per-phase time-varying windows | Output datasets (OUTEST=, OUTVCOV=) | Density / quantile prediction types | Previously listed gaps that have since been closed | Rcpp acceleration note | References

Kaplan-Meier baseline | Prediction types | Parametric survival with KM overlay | Confidence limits on predictions | Decomposed multiphase hazard | Multiphase survival with KM overlay | Patient-specific risk profiles | Multi-endpoint visualization: valves

Overview | Source file organization | Function call graph | Key internal functions | Theta vector layout | Phase specification | Decomposition engine | Multi-start optimization | Golden fixture system | Fixture format | Current fixtures | Regenerating fixtures | Testing strategy | Multiphase parity tests | Dataset catalog | Loading datasets | Dataset details | AVC (atrioventricular canal repair) | CABG/KUL (coronary artery bypass grafting) | OMC (open mitral commissurotomy) | TGA (transposition of great arteries) | Valves (primary valve replacement) | SAS/C parameter mapping | Early phase (G1) mapping | Late phase (G3) mapping | Version history | References