Function reference • tidyrgeoda

All functions

gzma: Guangzhou Metropolitan Social Space Quality Score Data

read_geoda(): Read A Geoda File(.gal,.gwt,.swm)

scale_fill_lisa(): LISA Fill Scales

st_azp_greedy(): A greedy algorithm to solve the AZP problem

st_azp_sa(): A simulated annealing algorithm to solve the AZP problem

st_azp_tabu(): A tabu algorithm to solve the AZP problem

st_breaks(): Univariate Spatial Stratification

st_contiguity_weights(): Contiguity Spatial Weights

st_distance_weights(): Distance-based Spatial Weights

st_kernel_knn_weights(): K-NN Kernel Spatial Weights

st_kernel_weights(): Distance-based Kernel Spatial Weights

st_knn_weights(): K-Nearest Neighbors-based Spatial Weights

st_lag(): Spatial Lag

st_lnmt(): Local Neighbor Match Test

st_local_bijoincount(): Bivariate Local Join Count Statistics

st_local_bimoran(): Bivariate Local Moran Statistics

st_local_g(): Local Getis-Ord's G Statistics

st_local_geary(): Local Geary Statistics

st_local_gstar(): Local Getis-Ord's G* Statistics

st_local_joincount(): Local Join Count Statistics

st_local_moran(): Local Moran Statistics

st_local_moran_eb(): Local Moran with Empirical Bayes(EB) Rate

st_local_multigeary(): Local Multivariate Geary Statistics

st_local_multijoincount(): (Multivariate) Colocation Local Join Count Statistics

st_local_multiquantilelisa(): Multivariate Quantile LISA Statistics

st_local_quantilelisa(): Quantile LISA Statistics

st_maxp_greedy(): A greedy algorithm to solve the max-p-region problem

st_maxp_sa(): A simulated annealing algorithm to solve the max-p-region problem

st_maxp_tabu(): A tabu-search algorithm to solve the max-p-region problem

st_redcap(): Regionalization with dynamically constrained agglomerative clustering and partitioning(REDCAP)

st_schc(): Spatially Constrained Hierarchical Clucstering (SCHC)

st_skater(): Spatial C(K)luster Analysis by Tree Edge Removal(SKATER)

st_summary(): Summary of Spatial Weights

st_weights(): Construct Spatial Weights

write_geoda(): Save Spatial Weights