SpatialInference
Tools for Statistical Inference with Geo-Coded Data
Fast computation of Conley (1999) <doi:10.1016/S0304-4076(98)00084-0> spatial heteroskedasticity and autocorrelation consistent (HAC) standard errors for linear regression models with geo-coded data, with a fast C++ implementation by Christensen, Hartman, and Samii (2021) <doi:10.1017/S0020818321000187>. Performance-critical distance calculations, kernel weighting, and variance component accumulation are implemented in C++ via 'Rcpp' and 'RcppArmadillo'. Includes tools for estimating the spatial correlation range from covariograms and correlograms following the bandwidth selection method proposed in Lehner (2026) <doi:10.48550/arXiv.2603.03997>, and diagnostic visualizations for bandwidth selection.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | SpatialInference_0.1.0.tar.gz |
1.1 MiB |
0.1.0 |
rolling linux/noble R-4.5 | SpatialInference_0.1.0.tar.gz |
1.1 MiB |
0.1.0 |
rolling source/ R- | SpatialInference_0.1.0.tar.gz |
1.0 MiB |
0.1.0 |
latest linux/jammy R-4.5 | SpatialInference_0.1.0.tar.gz |
1.1 MiB |
0.1.0 |
latest linux/noble R-4.5 | SpatialInference_0.1.0.tar.gz |
1.1 MiB |
0.1.0 |
latest source/ R- | SpatialInference_0.1.0.tar.gz |
1.0 MiB |
0.1.0 |
2026-04-26 source/ R- | SpatialInference_0.1.0.tar.gz |
1.0 MiB |
0.1.0 |
2026-04-23 source/ R- | SpatialInference_0.1.0.tar.gz |
1.0 MiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | SpatialInference_0.1.0.zip |
1.4 MiB |