Changes in version 0.2.2                        

P3 now applies MCP to delta / se_delta, with lambda and gamma defined on
that standardized scale. The smooth penalty integrates its slope to
(sqrt(delta^2 + eps^2) - eps) / se_delta; eps remains in log-HR units.
The transition half-width is rho_mcp * gamma_mcp * lambda in SE units.
Both derivative chain factors are included in the raw curvature;
negative curvature is still clipped only for the sandwich bread. The
optimizer includes transition points and refines all detected local
minima for P3.

This is a substantive replacement: recalibrate and reevaluate P3.
Previous P3 lambdas, estimates, and result files do not describe this
method. Other penalties and the fixed independent censoring design are
unchanged. The returned lambda_eff is retained as the origin slope
lambda / se_delta; it is no longer the lambda argument supplied to the
MCP primitive.

                        Changes in version 0.2.1                        

  - Censoring now uses a fixed exponential rate calculated from the
    internal population distribution, independent of realized replicate
    event times. Added calibrate_censor_rate() and optional censor_rate.
    Target zero yields exactly no censoring. Removed the stochastic
    per-replicate rate search.
  - Simulation and calibration pass the resolved fixed rate to every
    replicate. Existing simulation results and calibrated lambdas must
    not be mixed with results from this revised generator.
  - Fit and simulation method labels now match the manuscript. Short
    calibration API keys Li/P1/P2/P3/P4 remain supported;
    method_labels() translates keys and legacy output labels for
    presentation.

                 Changes in version 0.2.0 (2026-10-04)                  

  - Prepare source for CRAN checks and regenerate help from roxygen
    comments.
  - Add optional keep_raw retention to curve and study workflows.
  - Include valid/missing counts and Monte Carlo standard errors in
    simulation summaries; keep rows for methods with entirely missing
    inference results.
  - Stop the study wrapper when calibration fails instead of
    substituting 0.20.
  - Honor explicit drift_set_confirm grids. NULL defaults to the
    calibration grid. Existing calls with identical
    calibration/confirmation grids retain their calibration target;
    calls previously passing a different ignored confirmation grid now
    use that grid and can produce different tuning.
  - Retain coarse candidates in the fine calibration search.
  - Default parallel runs to two workers, propagate installed library
    paths, clean up failed cluster initialization, and support NULL
    seeds in wrappers.
  - Document conditional model-based SEs, approximate sandwich
    inference, finite-grid calibration, residual undercoverage and
    signed ESS gains.
  - Penalty formulas and fixed-lambda fitting algorithms are unchanged
    by this release-preparation pass. Earlier manuscript changes to
    P2/P3 still require recomputation of results from the original
    penalty definitions.

Methodology updates

  - Replace P2 drift-times-gate with the manuscript integrated-gate
    penalty.
  - Smooth the MCP origin and flat-tail transition; expose rho_mcp
    (default 0.1) through fitting, calibration and study workflows.
  - Match raw analytic curvature to the fitted penalties; retain
    clipping only in the plug-in variance calculation.
  - Support no-covariate Cox fits and simulation (p = 0).
  - Old P2/P3 fits and calibration results require recomputation.

                        Changes in version 0.1.0                        

  - Initial release.
  - User-facing functions: simulate_hybrid_cox, fit_internal_only,
    fit_naive_pooled, fit_li_adaptive_lasso, fit_P1_precision_L1,
    fit_P2_gated_L1, fit_P3_info_MCP, fit_P4_LRweighted_L1,
    fit_all_methods, fit_one_penalized_method, compute_sandwich_se,
    run_simulation, run_drift_curve, compute_ess_from_raw,
    add_ess_to_simulation_result, make_drift_set,
    make_drift_set_from_values, calibrate_lambda_grid,
    calibrate_lambda_grid_two_stage, calibrate_all_lambdas, and
    run_fdb_study.
  - Reference scenario scenario_S1 and default tuning list
    lambdas_default exported for examples and tests.