Package: lctools 0.3

lctools: Local and Geographically Weighted Spatial Statistics Tools

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) <doi:10.1007/s10037-011-0061-y>, Kalogirou (2016) <doi:10.1111/gean.12092>, and Rey and Smith (2013) <doi:10.1007/s12076-012-0086-z>.

Authors:Stamatis Kalogirou [aut, cre]