Local and Geographically Weighted Spatial Statistics Tools
Description
Provides researchers and educators with easy-to-learn, user friendly
tools for calculating key spatial statistics and for applying simple as well as
advanced methods of spatial analysis on real data. These include: Local Pearson
and Geographically Weighted Pearson Correlation Coefficients; Spatial Inequality
Measures (Gini coefficient, Spatial Gini, Location Quotient (LQ) and Focal
Location Quotient); Spatial Autocorrelation indices (Global and Local Moran's I);
several Geographically Weighted Regression techniques, including the
Geographically Weighted Zero-Inflated Poisson Regression; tools for computing
variables used in Spatial Interaction Models; and other spatial analysis tools
(other geographically weighted statistics). The local correlation tools were
originally developed to test for local multicollinearity among the explanatory
variables of local regression models and can also be used to examine the local
association between pairs of variables. The package also contains functions for
measuring the significance of each statistic calculated, mainly based on Monte
Carlo simulations, and comes with two example datasets, one of which is a spatial
data frame referring to the municipalities of Greece. Methods are described in
Kalogirou (2012) , Kalogirou (2016)
, and Rey and Smith (2013) .