# Spatial Data Science Complementary Features

## Documentation for package ‘sdsfun’ version 0.8.1

- DESCRIPTION file.
- Package NEWS.

## Help Pages

check_tbl_na | check for NA values in a tibble
cor_test | (partial) correlation test
discretize_vector | discretization
dummy_tbl | transforming a category tibble into the corresponding dummy variable tibble
dummy_vec | transforming a categorical variable into dummy variables
formula_varname | get variable names in a formula and data
fuzzyoverlay | spatial fuzzy overlay
generate_subsets | generate subsets of a set
geodetector_q | only geodetector q-value
hclustgeo_disc | hierarchical clustering with spatial soft constraints
inverse_distance_swm | construct inverse distance weight
loess_optnum | determine optimal spatial data discretization for individual variables
moran_test | global spatial autocorrelation test
normalize_vector | normalization
rm_lineartrend | remove variable linear trend based on covariate
sf_coordinates | extract locations
sf_distance_matrix | generates distance matrix
sf_geometry_name | sf object geometry column name
sf_geometry_type | sf object geometry type
sf_gk_proj_cgcs2000 | generates cgcs2000 Gauss-Kruger projection epsg coding character
sf_utm_proj_wgs84 | generates wgs84 utm projection epsg coding character
sf_voronoi_diagram | generates voronoi diagram
spade_psd | only spade power of spatial determinant
spdep_contiguity_swm | constructs spatial weight matrices based on contiguity
spdep_distance_swm | constructs spatial weight matrices based on distance
spdep_lmtest | spatial linear models selection
spdep_nb | construct neighbours list
spdep_skater | spatial c(k)luster analysis by tree edge removal
spvar | spatial variance
ssh_test | spatial stratified heterogeneity test
standardize_vector | standardization
tbl_all2int | convert discrete variables in a tibble to integers
tbl_xyz2mat | convert xyz tbl to matrix