Spatial Distribution Dynamics // A tidy toolkit for distribution dynamics: analysing how a cross-sectional distribution of values evolves over time and where it settles in the long run. Provides discrete-time, spatial, rank and local indicator of spatial association ('LISA') Markov transition estimation, ergodic analysis (steady-state, mean first passage and sojourn times), rank-mobility measures (Kendall's tau and the Theta statistic) and Markov mobility indices. Methods use long-format 'id'/'time'/'value' data rather than transition matrices and build on the distribution-dynamics literature (Quah (1993); Rey (2001) doi:10.1111/j.1538-4632.2001.tb00444.x). Results are validated for numerical parity against the reference 'giddy' library.