The heterogeneity of spatial data presenting a finite number of categories can be measured via computation of spatial entropy. Functions are available for the computation of the main entropy and spatial entropy measures in the literature. They include the traditional version of Shannon's entropy (Shannon, 1948 <doi:10.1002/j.1538-7305.1948.tb01338.x>), Batty's spatial entropy (Batty, 1974 <doi:10.1111/j.1538-4632.1974.tb01014.x>), O'Neill's entropy (O'Neill et al., 1998 <doi:10.1007/BF00162741>), Li and Reynolds' contagion index (Li and Reynolds, 1993 <doi:10.1007/BF00125347>), Karlstrom and Ceccato's entropy (Karlstrom and Ceccato, 2002 <urn:nbn:se:kth:diva-61351>), Leibovici's entropy (Leibovici, 2009 <doi:10.1007/978-3-642-03832-7_24>), Parresol and Edwards' entropy (Parresol and Edwards, 2014 <doi:10.3390/e16041842>) and Altieri's entropy (Altieri et al., 2018, <doi:10.1007/s10651-017-0383-1>). Full references for all measures can be found under the topic 'SpatEntropy'. The package is able to work with lattice and point data. The updated version works with the updated 'spatstat' package (>= 3.0-2).

Regularized Spatial Maximum Covariance Analysis
Provide regularized maximum covariance analysis incorporating smoothness, sparseness and orthogonality of couple patterns by using the alternating direction method of multipliers algorithm. The method can be applied to either regularly or irregularly spaced data.

Provide regularized maximum covariance analysis incorporating smoothness,
sparseness and orthogonality of couple patterns by using the alternating direction method
of multipliers algorithm. The method can be applied to either regularly or irregularly
spaced data (Wang and Huang, 2017).
Rcpp, RcppParallel (>= 0.11.2), fields, MASS
Wen-Ting Wang [aut, cre], Hsin-Cheng Huang [aut]

Provide regularized maximum covariance analysis incorporating smoothness,
sparseness and orthogonality of couple patterns by using the alternating direction method
of multipliers algorithm. The method can be applied to either regularly or irregularly
spaced data,  including 1D, 2D, and 3D (Wang and Huang, 2017 <doi:10.1002/env.2481>).