Changes in version 0.1.0 (2026-05-30)                  

Initial CRAN release.

Workflow

  - classify_dynamics(), markov_dynamics(), spatial_markov(), and
    rank_mobility() accept long sf panels keyed by explicit id, time,
    and value columns.
  - transition_matrix(), steady_state(), class_intervals(), and
    lag_intervals() provide tidy access to results.
  - plot_transition_matrix(), plot_spatial_markov(), and
    plot_rank_mobility() return ggplot2 objects.

Spatial weights

  - spatial_markov() accepts a geometry argument: an sf tibble with one
    row per spatial unit and nb / wt list-columns produced by sfdep.
    This is the preferred input. listw and nb arguments remain accepted
    for compatibility with prior workflows and oracle comparisons.

Data

  - Bundled usjoin: 48 contiguous US state per-capita personal income,
    1929–2009, mirroring PySAL's reference dataset for spatial Markov
    examples.

Validation

  - Static fixtures cross-checked against estdaR::sp.mkv() and
    spdyn::spMarkov(). Optional live cross-checks run when those
    packages or PySAL giddy are installed.