sddr 0.1.1

• Initial CRAN release.
• Removed an unresolvable DOI from the Quah (1993) reference.
• markov(): classic discrete-time, first-order Markov transition estimation from tidy long-format id/time/value panel data, with quantile-based (fixed or per-period) class discretisation.
• full_rank_markov() and geo_rank_markov(): rank-based Markov chains (ranks-as-states, and units-exchanging-rank-positions) — no binning required.
• lisa_markov(): Markov chain over the four Moran-scatterplot quadrants (HH/LH/LL/HL), capturing the joint dynamics of a unit and its neighbourhood.
• spatial_markov(): spatial Markov chain (Rey 2001) with transition matrices conditioned on the spatial-lag class of the neighbourhood. Accepts either a spatial weights matrix (lag computed internally) or a precomputed lag column, and explicit breaks / lag_breaks cut points. With matching cut points it reproduces PySAL giddy’s spatial Markov matrices to machine precision.
• steady_state(): ergodic / stationary distribution of a transition matrix or an sddr_markov object.
• mfpt(): mean first passage times (Kemeny-Snell fundamental matrix), with mean recurrence times on the diagonal.
• sojourn_time(): expected persistence time in each class.
• tau(): Kendall’s tau rank correlation (positional / exchange mobility), with concordant/discordant counts and an asymptotic p-value.
• theta(): Theta rank-mobility statistic (Rey 2004) decomposing rank change by regime.
• tau_local(): per-observation (local) Kendall’s tau decomposition.
• mobility(): Markov mobility indices (Prais, determinant, second-eigenvalue L2, and the Shorrocks B1/B2 indices).
• print() methods for sddr_markov and sddr_spatial_markov.
• spatial_markov() and lisa_markov() now accept spatial weights as an listw or nb object (e.g. built from an sf layer), in addition to a plain weights matrix. ‘spdep’ is an optional (Suggests) dependency.
• Hex logo, pkgdown site configuration, and GitHub Actions R-CMD-check CI.