Changes in version 0.2.0                        

  - New estimation and testing functions:
      - rmst_fast(): restricted mean survival time for a single group or
        a two-group comparison (difference and ratio contrasts),
        integrating the Kaplan-Meier survival step function in a single
        C++ scan.
      - milestone_fast(): two-group comparison of Kaplan-Meier survival
        at a milestone timepoint, with Wald, log-log, and MOVER
        inference methods.
      - maxcombo_fast(): max-combo test over a set of Fleming-Harrington
        weighted log-rank statistics, with the joint p-value obtained
        from the implied multivariate normal distribution.
      - rmw_fast(): robust modestly-weighted log-rank test of Magirr and
        Öhrn, the maximum of the standard log-rank and a
        modestly-weighted log-rank statistic, with the joint p-value
        obtained from the implied bivariate normal distribution.
      - ahsw_fast(): average hazard with survival weight of Uno and
        Horiguchi, reporting the ratio (RAH) and difference (DAH)
        contrasts.
      - ahr_fast(): Kalbfleisch-Prentice average hazard ratio between
        two groups over a restricted interval, the estimator used by
        Dormuth et al. (2024) for sample-size calculation under
        non-proportional hazards, with a test on the group-share scale
        and an equivalent test and confidence interval on the log scale.
  - survdiff_fast() gains weighted log-rank tests (Fleming-Harrington,
    modestly-weighted, Gehan-Breslow, Tarone-Ware) and stratified and
    stratified-weighted variants, all sharing the single-scan C++
    backend.
  - New simulation layer:
      - simdata_fast() extended with optional subgroups defined by a
        prevalence specification and a flexible accrual specification:
        a.rate gives absolute accrual rates (with the end of an open
        final interval solved from the total when a trailing rate is
        supplied) and a.prop gives accrual proportions, with
        deterministic per-interval accrual counts. The entire generation
        pipeline runs in a single C++ kernel that materializes the
        output data frame once.
      - analysis_fast(): interim or sequential analysis of simulated
        data at one or more looks, defined by target event counts or
        calendar times, computed by a fused C++ kernel that reuses the
        analysis cores of the standalone functions. Supports subgroup
        analyses.
      - simsummary_fast(): operating-characteristic summary (rejection
        and futility rates, stopping-look distribution, expected timing)
        from analysis_fast() output and supplied group-sequential
        boundaries, with a print() method that lays the results out as a
        group-sequential design report.
  - Each estimation and testing function has a corresponding print()
    method, and the print methods share a unified display format.

                 Changes in version 0.1.0 (2026-05-27)                  

  - Initial release.
  - Core computations implemented in C++ via Rcpp for use inside large
    simulation loops.
  - survfit_fast(): single-time-point Kaplan-Meier estimator with
    Greenwood standard error and plain / log / log-log confidence
    intervals. The C++ backend locates the evaluation cutoff via binary
    search and accumulates the Kaplan-Meier product and Greenwood
    variance sum in a single scan over event positions. Returns an
    object of class "survfit_fast" with a print() method.
  - survdiff_fast(): log-rank test returning a one-sided Z-score or a
    two-sided chi-square statistic. The C++ backend uses a two-pointer
    merge scan over pooled sorted vectors, eliminating the rank
    construction, tabulate(), and reverse cumulative sum operations of
    the standard implementation. Returns an object of class
    "survdiff_fast" with a print() method.
  - coxph_fast(): closed-form hazard ratio estimator via the Pike-Halley
    Estimator method with Wald confidence interval. The C++ backend
    performs group splitting, at-risk counting, and
    per-distinct-event-time accumulation in a single pass. Returns an
    object of class "coxph_fast" with a print() method.
  - simdata_fast(): clinical trial data simulator supporting one- and
    two-group designs, piecewise uniform accrual, and simple and
    piecewise exponential survival and dropout times. C++ backends
    handle piecewise sampling and two-group interleaving, and random
    number generation uses dqrng.