Spatial Data Science Complementary Features

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Documentation for package ‘sdsfun’ version 0.8.0

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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