SuperSurv 0.1.9
CRAN release: 2026-10-02
Changes since the previous CRAN release, 0.1.7.
Backward-Compatibility Summary
The default survival transformation remains exponential. The following changes can affect existing analyses or function calls.
Fitting and prediction
- Direct simplex optimization can change ensemble weights relative to normalized nonnegative least squares (NNLS).
- Corrected tied-event calibration can change calibrated survival predictions and ensemble weights on data with tied event times.
- Right-continuous censoring endpoint corrections can change fitted weights at grid points coinciding with observed censoring times.
- Models can now be fitted without supplying prediction data or prediction times. Existing calls that supply both arguments remain supported.
- Product-limit conversion is opt-in; exponential conversion remains the default.
-
metalearner = "entropy"remains temporarily available with a deprecation warning. Use"brier"or"logloss"for new analyses. - Single-patient and single-time forest predictions retain their documented matrix dimensions.
Evaluation and interpretation
- Corrected reverse Kaplan-Meier tie handling can change evaluation metrics on data with tied event and censoring times.
- RMST point contrasts remain available. The standard error, confidence interval, and p-value are no longer returned;
inference = TRUEnow produces an error. - The optional SHAP backend is now
kernelshap, andexplain_kernel()requires an expliciteval_time. Explanations target the fitted ensemble’s event probability at that time rather than a composite of native learner scores. The output table structure is retained, but earlier numerical SHAP results are not comparable. Recompute explanations with an explicitly chosen horizon.