Functionality for exploratory data analysis and nonparametric analysis
of spatial data, mainly spatial point patterns, in the 'spatstat'
family of packages. (Excludes analysis of spatial data on a linear
network, which is covered by the separate package 'spatstat.linnet'.)
Methods include quadrat counts, K-functions and their simulation
envelopes, nearest neighbour distance and empty space statistics, Fry
plots, pair correlation function, kernel smoothed intensity, relative
risk estimation with cross-validated bandwidth selection, mark
correlation functions, segregation indices, mark dependence
diagnostics, and kernel estimates of covariate effects. Formal
hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov,
Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte
Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson,
Kolmogorov-Smirnov, ANOVA) are also supported.