R Library for Spatial Data Analysis


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Documentation for package ‘rgeoda’ version 0.0.10-4

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$-method p_GeoDa
$-method p_GeoDaTable
$-method p_GeoDaWeight
$-method p_LISA
as.data.frame.geoda convert rgeoda instance to data.frame
as.geoda Create an instance of geoda-class from either an 'sf' or 'sp' object
as.matrix.Weight spatial weights to matrix
azp_greedy A greedy algorithm to solve the AZP problem
azp_sa A simulated annealing algorithm to solve the AZP problem
azp_tabu A tabu algorithm to solve the AZP problem
create_weights Create an empty weights
distance_weights Distance-based Spatial Weights
eb_rates Empirical Bayes(EB) Rate
gda_distance_weights (For internally use and test only) Distance-based Spatial Weights
gda_kernel_knn_weights (For internally use and test only) K-NN Kernel Spatial Weights
gda_kernel_weights (For internally use and test only) Distance-based Kernel Spatial Weights
gda_knn_weights (For internally use and test only) K-Nearest Neighbors-based Spatial Weights
gda_min_distthreshold (For internally use and test only) Minimum Distance Threshold for Distance-based Weights
gda_queen_weights (For internally use and test only) Queen Contiguity Spatial Weights
gda_rook_weights (For internally use and test only) Rook Contiguity Spatial Weights
geoda 'geoda' class
geoda-class 'geoda' class
geoda_open Create an instance of geoda-class by reading from an ESRI Shapefile dataset
get_neighbors Neighbors of one observation
get_neighbors_weights Weights values of the neighbors of one observation
has_isolates Isolation/Island in Spatial Weights
hinge15_breaks (Box) Hinge15 Breaks
hinge30_breaks (Box) Hinge30 Breaks
is_symmetric Symmetry of Weights Matrix
join_count_ratio Join Count Ratio
kernel_knn_weights K-NN Kernel Spatial Weights
kernel_weights Distance-based Kernel Spatial Weights
knn_weights K-Nearest Neighbors-based Spatial Weights
LISA LISA class (Internally Used)
LISA-class LISA class (Internally Used)
lisa_bo Bonferroni bound value of local spatial autocorrelation
lisa_clusters Get local cluster indicators
lisa_colors Get cluster colors
lisa_fdr False Discovery Rate value of local spatial autocorrelation
lisa_labels Get cluster labels
lisa_num_nbrs Get numbers of neighbors for all observations
lisa_pvalues Get pseudo-p values of LISA
lisa_values Get LISA values
local_bijoincount Bivariate Local Join Count Statistics
local_bimoran Bivariate Local Moran Statistics
local_g Local Getis-Ord's G Statistics
local_geary Local Geary Statistics
local_gstar Local Getis-Ord's G* Statistics
local_joincount Local Join Count Statistics
local_moran Local Moran Statistics
local_moran_eb Local Moran with Empirical Bayes(EB) Rate
local_multigeary Local Multivariate Geary Statistics
local_multijoincount (Multivariate) Colocation Local Join Count Statistics
local_multiquantilelisa Multivariate Quantile LISA Statistics
local_quantilelisa Quantile LISA Statistics
make_spatial Make Spatial
maxp_greedy A greedy algorithm to solve the max-p-region problem
maxp_sa A simulated annealing algorithm to solve the max-p-region problem
maxp_tabu A tabu-search algorithm to solve the max-p-region problem
max_neighbors Maximum Neighbors of Spatial Weights
mean_neighbors Mean Neighbors of Spatial Weights
median_neighbors Median Neighbors of Spatial Weights
min_distthreshold Minimum Distance Threshold for Distance-based Weights
min_neighbors Minimum Neighbors of Spatial Weights
natural_breaks Natural Breaks (Jenks)
neighbor_match_test Local Neighbor Match Test
percentile_breaks Percentile Breaks
p_GeoDa p_GeoDa
p_GeoDa-class p_GeoDa
p_GeoDaTable p_GeoDaTable
p_GeoDaTable-class p_GeoDaTable
p_GeoDaWeight p_GeoDaWeight
p_GeoDaWeight-class p_GeoDaWeight
p_LISA p_LISA
p_LISA-class p_LISA
quantile_breaks Quantile Breaks
queen_weights Queen Contiguity Spatial Weights
read_gal Read a .GAL file
read_gwt Read a .GWT file
read_swm Read a .SWM file
redcap Regionalization with dynamically constrained agglomerative clustering and partitioning
rook_weights Rook Contiguity Spatial Weights
save_weights Save Spatial Weights
schc Spatially Constrained Hierarchical Clucstering (SCHC)
set_neighbors Set neighbors of an observation
set_neighbors_with_weights Set neighbors and weights values of an observation
sf_to_geoda Create an instance of geoda-class from a 'sf' object
skater Spatial C(K)luster Analysis by Tree Edge Removal
spatial_lag Spatial Lag
spatial_validation Spatial Validation
sp_to_geoda Create an instance of geoda-class from a 'sp' object
stddev_breaks Standard Deviation Breaks
summary.Weight Summary of Spatial Weights
update_weights Update meta data of a spatial weights
Weight Weight class (Internally Used)
Weight-class Weight class (Internally Used)
weights_sparsity Sparsity of Spatial Weights