Changes in version 0.4                         

Testing Infrastructure

  - Migrated test suite to testthat framework in standard R package
    location (tests/testthat/).
  - Tests now run automatically during R CMD check.
  - Added skip_if_no_jax() helper for graceful skipping when JAX is
    unavailable.
  - Test files organized by category:
      - test-pure-r.R: Pure R implementation tests (always run)
      - test-jax-integration.R: JAX-accelerated function tests
      - test-distance.R: Distance metric tests
      - test-edge-cases.R: Boundary condition tests

                  Changes in version 0.3 (2025-12-22)                   

New Features

  - Added diagnose_rerandomization() function for pre-analysis
    evaluation of rerandomization designs. This function helps
    researchers determine optimal acceptance thresholds by computing:
    
      - Expected number of acceptable randomizations
      - Minimum balance criterion values
      - Power analysis for different threshold choices

  - Added fast_distance() function for hardware-accelerated pairwise
    distance computation supporting multiple metrics: Euclidean,
    Manhattan, Mahalanobis, cosine, and correlation-based distances.

  - Added S3 methods (print, summary, plot) for
    fastrerandomize_diagnostic class to visualize and summarize
    diagnostic results.

Improvements

  - Updated JAX backend to support CUDA 12 and CUDA 13.
  - Improved documentation throughout the package.
  - Various bug fixes and performance improvements.

                  Changes in version 0.2 (2025-01-14)                   

Initial CRAN Release (2025-01-14)

First release on CRAN with core functionality:

  - generate_randomizations(): Generate pools of acceptable
    randomizations based on covariate balance.
  - generate_randomizations_exact(): Exact enumeration for small
    experiments.
  - generate_randomizations_mc(): Monte Carlo sampling for larger
    experiments.
  - randomization_test(): Permutation-based inference with optional
    fiducial intervals.
  - build_backend(): Create conda environment with JAX and GPU support.
  - check_jax_availability(): Verify JAX backend availability.
  - Pure R fallback implementations (_R suffix functions) for
    environments without JAX.
  - Support for CPU, CUDA, and METAL hardware acceleration frameworks.
  - S3 classes with print, summary, and plot methods for results
    objects.
  - Included datasets: QJEData and YOPData.