slxr 0.1.1

CRAN resubmission addressing feedback from the initial submission.

• Added \value sections to slx-tidiers.Rd (documenting the tibble columns returned by tidy.slx() and glance.slx()) and slx_sensitivity.Rd (documenting that the stub is called for its side effect of signalling an error, with a note on the planned future return value).
• Removed all \dontrun{} blocks from examples. Examples in slx-tidiers, slx_effects, slx_plot_effects, and slx_plot_shock are now unwrapped and run against the bundled defense_burden dataset. The slx_weights example now runs a custom-matrix case by default; the optional sf-based contiguity example is wrapped in \donttest{} and guarded by requireNamespace().

slxr 0.1.0

Initial CRAN release.

Core

• slx() fits Spatial-X regression models of the form y = X*beta + WX*theta + epsilon via OLS on an augmented design matrix, with a formula interface and first-class support for variable-specific weights matrices.
• slx_weights() constructs slx_W weights objects from sf input (contiguity, rook, knn, distance) or from a user-supplied matrix (custom).
• slx_effects() returns a tidy tibble with direct, indirect, and total effects and their standard errors.
• Higher-order spatial lags (order = 1:k) supported.

Panel support

• id and time arguments turn slx() into a panel estimator. Weights matrices can be time-invariant or supplied as named year-keyed lists. Unbalanced panels are handled automatically.
• time_lag = k implements the temporally-lagged spatial lag (TSLS, equation 7 of Wimpy, Whitten, and Williams 2021).

Interpretation and visualization

• slx_compare() produces side-by-side fit statistics for lm and slx objects, with optional Moran’s I on residuals.
• slx_plot_effects(), slx_plot_decay(), slx_plot_shock(), and slx_plot_W() return ggplot objects that can be further customized with + geom_*() / + theme_*().
• tidy() and glance() methods for compatibility with the broom and modelsummary ecosystems.

Data

• defense_burden: 1995 cross-section of 179 countries with three sparse weights matrices (contiguity, alliance, defense pact).
• defense_burden_panel: 1951-2008 panel (7,661 observations) with year-specific sparse weights matrices.

Both datasets are drawn from the replication archive for Wimpy, Whitten, and Williams (2021), Journal of Politics 83(2): 722-739.