Performs simulations of binary spatial raster data using
    the Ising model (Ising (1925) <doi:10.1007/BF02980577>; 
    Onsager (1944) <doi:10.1103/PhysRev.65.117>). It allows to set a few
    parameters that represent internal and external pressures, and the number 
    of simulations (Stepinski and Nowosad (2023) <doi:10.1098/rsos.231005>).

Calculate Kernel Density Estimation (KDE) for spatial data. 
  The algorithm is inspired by the tool 'Heatmap' from 'QGIS'. The method is described by:
  Hart, T., Zandbergen, P. (2014) <doi:10.1108/PIJPSM-04-2013-0039>, 
  Nelson, T. A., Boots, B. (2008) <doi:10.1111/j.0906-7590.2008.05548.x>,
  Chainey, S., Tompson, L., Uhlig, S.(2008) <doi:10.1057/palgrave.sj.8350066>.

Implements a spatial extension of the random forest algorithm
    (Georganos et al. (2019) <doi:10.1080/10106049.2019.1595177>). Provides
    a Geographically Weighted Random Forest regression and a routine to
    find the optimal bandwidth (Georganos and Kalogirou (2022)
    <doi:10.3390/ijgi11090471>). A lightweight cross-validation helper for
    tuning the 'mtry' parameter of a random forest and a generator of
    synthetic spatial test data are also included. The package depends on
    'ranger' as its single random-forest back-end.

Test and estimates of location, tests of independence, tests of sphericity and several estimates of shape all based on spatial signs, symmetrized signs, ranks and signed ranks. For details, see Oja and Randles (2004) <doi:10.1214/088342304000000558> and Oja (2010) <doi:10.1007/978-1-4419-0468-3>.

Tools to assess the association between two spatial processes. Currently,
  several methodologies are implemented: A modified t-test to perform hypothesis testing
  about the independence between the processes, a suitable nonparametric correlation
  coefficient, the codispersion coefficient, and an F test for assessing the multiple
  correlation between one spatial process and several others. Functions for image
  processing and computing the spatial association between images are also provided.
  Functions contained in the package are intended to accompany Vallejos, R., Osorio, F.,
  Bevilacqua, M. (2020). Spatial Relationships Between Two Georeferenced Variables:
  With Applications in R. Springer, Cham <doi:10.1007/978-3-030-56681-4>.