Spatial Dependence: Weighting Schemes and Statistics
A collection of functions to create spatial weights matrix objects from polygon 'contiguities', from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree; a collection of tests for spatial 'autocorrelation', including global 'Morans I' and 'Gearys C' proposed by 'Cliff' and 'Ord' (1973, ISBN: 0850860369) and (1981, ISBN: 0850860814), 'Hubert/Mantel' general cross product statistic, Empirical Bayes estimates and 'Assunção/Reis' (1999) https://doi.org/10.1002/(SICI)1097-0258(19990830)18:16%3C2147::AID-SIM179%3E3.0.CO;2-I Index, 'Getis/Ord' G ('Getis' and 'Ord' 1992) https://doi.org/10.1111/j.1538-4632.1992.tb00261.x and multicoloured join count statistics, 'APLE' ('Li 'et al.' ) https://doi.org/10.1111/j.1538-4632.2007.00708.x, local 'Moran's I' (Anselin 1995) https://doi.org/10.1111/j.1538-4632.1995.tb00338.x and 'Getis/Ord' G ('Ord' and 'Getis' 1995) https://doi.org/10.1111/j.1538-4632.1995.tb00912.x, 'saddlepoint' approximations ('Tiefelsdorf' 2002) https://doi.org/10.1111/j.1538-4632.2002.tb01084.x and exact tests for global and local 'Moran's I' ('Bivand et al.' 2009) https://doi.org/10.1016/j.csda.2008.07.021 and 'LOSH' local indicators of spatial heteroscedasticity ('Ord' and 'Getis') https://doi.org/10.1007/s00168-011-0492-y. The implementation of most of the measures is described in 'Bivand' and 'Wong' (2018) https://doi.org/10.1007/s11749-018-0599-x.
spdep >= 1.1-1 corresponds to spatialreg >= 1.1-1, in which the model fitting functions are deprecated and pass through to spatialreg, but will mask those in spatialreg. From versions 1.2-1, the functions will be made defunct in spdep.
For now spatialreg only has functions from spdep, where they are shown as deprecated. spatialreg only loads the namespace of spdep; if you attach it, the same functions in the other package will be masked. Some feed through adequately, others do not (mostly where
stats::model.matrix() facilities do not like the extra level of passing arguments).
Moved from R-Forge