When the input x is a factor or a
character, discretize_vector causes R to crash
(#12).
Implement the formula_varname function to return the
corresponding variable names from both formula and
data.
Improve the handling of n-level categorical
variables by generating n-1 dummy variables (#2).
Add the spdep_lmtest function for spatial linear
model selection (#3).
Migrate the moran_test function from the
geocomplexity package to sdsfun (#4).
Implement the geographical detector’s factor detector in
ssh_test using Rcpp to enhance performance
(#5).
Introduce the discretize_vector function to support
variable discretization (#6).
Apply the loess_optnum function to select the
optimal number of discretization intervals (#10).
Implement spatial variance calculation in the spvar
function, with support for both R and C++
implementations (#11).
Rename dummy_vector to dummy_vec for
consistency in naming conventions.
Add the sf_coordinates function to extract
coordinates from sf objects.
Begin to use Rcpp to complete some tasks with high
computational complexity.
Add dummy_vector and dummy_tbl
functions for dummy variables generation.
Add spdep_nb function for neighbours list
generation.
Add spdep_skater function for spatial constrained
clustering.
Add fuzzyoverlay function for spatial fuzzy
overlay.
Update package extdata; now sdsfun has two extdata:
gzma.gpkg and pts.gpkg.
Enhance support for other types of spatial vector data.
Inhibit the warning information produced by
spdep.
Add sf_utm_proj_wgs84() function.
sf_distance_matrix() function.Update the function documentation for
spdep_contiguity_swm() and
spdep_distance_swm().
Move the source code from SpatLyu/sdsfun on GitHub
to stscl/sdsfun.