rgeoda0.0.10-4 package

R Library for Spatial Data Analysis

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 Weigh...

gda_knn_weights

(For internally use and test only) K-Nearest Neighbors-based Spatial W...

gda_min_distthreshold

(For internally use and test only) Minimum Distance Threshold for Dist...

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-class

'geoda' class

geoda_open

Create an instance of geoda-class by reading from an ESRI Shapefile da...

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-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

max_neighbors

Maximum Neighbors of Spatial Weights

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

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

p_GeoDa-class

p_GeoDa

p_GeoDaTable-class

p_GeoDaTable

p_GeoDaWeight-class

p_GeoDaWeight

p_LISA-class

p_LISA

percentile_breaks

Percentile Breaks

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 ...

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

sp_to_geoda

Create an instance of geoda-class from a 'sp' object

spatial_lag

Spatial Lag

spatial_validation

Spatial Validation

stddev_breaks

Standard Deviation Breaks

summary.Weight

Summary of Spatial Weights

update_weights

Update meta data of a spatial weights

Weight-class

Weight class (Internally Used)

weights_sparsity

Sparsity of Spatial Weights

Provides spatial data analysis functionalities including Exploratory Spatial Data Analysis, Spatial Cluster Detection and Clustering Analysis, Regionalization, etc. based on the C++ source code of 'GeoDa', which is an open-source software tool that serves as an introduction to spatial data analysis. The 'GeoDa' software and its documentation are available at <https://geodacenter.github.io>.

  • Maintainer: Xun Li
  • License: GPL (>= 2)
  • Last published: 2023-07-01