r-spatial/spdep: Spatial Dependence: Weighting Schemes, Statistics and Models

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', 'APLE', 'Gearys C', 'Hubert/Mantel' general cross product statistic, Empirical Bayes estimates and 'Assunção/Reis' Index, 'Getis/Ord' G and multicoloured join count statistics, local 'Moran's I' and 'Getis/Ord' G, 'saddlepoint' approximations, exact tests for global and local 'Moran's I' and 'LOSH' local indicators of spatial heteroscedasticity; and functions for estimating spatial simultaneous 'autoregressive' ('SAR') lag, error, general nested spatial and 'SARAR' models using maximum likelihood and 'MCMC', impact measures for lag, spatial 'Durbin', 'SLX', spatial 'Durbin' error, 'SARAR' and 'GNS' models, weighted and 'unweighted' 'SAR' and 'CAR' spatial regression models, semi-parametric and Moran 'eigenvector' spatial filtering, 'GM SAR' error models, and generalized spatial two stage least squares models.

install.packages("devtools")
library(devtools)
install_github("r-spatial/spdep")