Changes in version 0.1.1                        

Bug fixes

  - Fixed cascading drift in correctHeaps() when using custom heap
    positions. When heaps were specified at consecutive integers (e.g.,
    heaps = seq(2, max(x), by = 1)), observations corrected for one heap
    could be picked up and re-corrected at subsequent heaps, causing
    values to drift far from their original position (reported by Saskia
    Schirmer).

  - Fixed R's sample() single-value trap in both correctHeaps() and
    correctSingleHeap(). When only one observation was available for
    correction at a heap, sample(n, size = 1) would sample from 1:n
    instead of returning n, potentially writing replacement values to
    wrong indices.

  - Added a warning when more than 50% of unique values in the data are
    declared as heaps, indicating likely misspecification of the heaps
    argument. Heaping correction is designed for sparse heap positions
    (e.g., multiples of 5 or 10), not for every value in the data.

                 Changes in version 0.1.0 (2026-02-09)                  

  - Initial release.
  - correctHeaps() and correctSingleHeap() for individual-level heaping
    correction using truncated log-normal, normal, uniform, or kernel
    density distributions.
  - Heaping indices: whipple(), myers(), bachi(), noumbissi(),
    spoorenberg(), coale_li(), jdanov(), kannisto(), and
    heaping_indices().
  - sprague() for disaggregating 5-year age groups using Sprague
    multipliers.
  - Support for sampling weights in all heaping indices.
  - Optional model-based correction using random forest predictions.
  - Vignette with comprehensive examples.