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rgeoda (version 0.0.11-1)

R Library for Spatial Data Analysis

Description

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 .

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Install

install.packages('rgeoda')

Monthly Downloads

2,368

Version

0.0.11-1

License

GPL (>= 2)

Issues

17

Pull Requests

0

Stars

73

Forks

14

Maintainer

Xun Li

Last Published

December 19th, 2024

Functions in rgeoda (0.0.11-1)

join_count_ratio

Join Count Ratio
has_isolates

Isolation/Island in Spatial Weights
knn_weights

K-Nearest Neighbors-based Spatial Weights
lisa_fdr

False Discovery Rate value of local spatial autocorrelation
hinge15_breaks

(Box) Hinge15 Breaks
kernel_weights

Distance-based Kernel Spatial Weights
lisa_colors

Get cluster colors
local_gstar

Local Getis-Ord's G* Statistics
local_quantilelisa

Quantile LISA Statistics
is_symmetric

Symmetry of Weights Matrix
kernel_knn_weights

K-NN Kernel Spatial Weights
local_joincount

Local Join Count Statistics
lisa_pvalues

Get pseudo-p values of LISA
lisa_num_nbrs

Get numbers of neighbors for all observations
lisa_labels

Get cluster labels
hinge30_breaks

(Box) Hinge30 Breaks
local_multiquantilelisa

Multivariate Quantile LISA Statistics
lisa_values

Get LISA values
local_bijoincount

Bivariate Local Join Count Statistics
local_bimoran

Bivariate Local Moran Statistics
gda_min_distthreshold

(For internally use and test only) Minimum Distance Threshold for Distance-based Weights
get_neighbors_weights

Weights values of the neighbors of one observation
get_neighbors

Neighbors of one observation
local_g

Local Getis-Ord's G Statistics
local_moran_eb

Local Moran with Empirical Bayes(EB) Rate
local_moran

Local Moran Statistics
local_geary

Local Geary Statistics
median_neighbors

Median Neighbors of Spatial Weights
lisa_bo

Bonferroni bound value of local spatial autocorrelation
set_neighbors_with_weights

Set neighbors and weights values of an observation
p_LISA-class

p_LISA
percentile_breaks

Percentile Breaks
min_neighbors

Minimum Neighbors of Spatial Weights
lisa_clusters

Get local cluster indicators
natural_breaks

Natural Breaks (Jenks)
read_gal

Read a .GAL file
rook_weights

Rook Contiguity Spatial Weights
save_weights

Save Spatial Weights
spatial_lag

Spatial Lag
read_gwt

Read a .GWT file
spatial_validation

Spatial Validation
queen_weights

Queen Contiguity Spatial Weights
max_neighbors

Maximum Neighbors of Spatial Weights
make_spatial

Make Spatial
quantile_breaks

Quantile Breaks
sf_to_geoda

Create an instance of geoda-class from a 'sf' object
update_weights

Update meta data of a spatial weights
weights_sparsity

Sparsity of Spatial Weights
local_multigeary

Local Multivariate Geary Statistics
local_multijoincount

(Multivariate) Colocation Local Join Count Statistics
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
p_GeoDaTable-class

p_GeoDaTable
min_distthreshold

Minimum Distance Threshold for Distance-based Weights
neighbor_match_test

Local Neighbor Match Test
redcap

Regionalization with dynamically constrained agglomerative clustering and partitioning
stddev_breaks

Standard Deviation Breaks
read_swm

Read a .SWM file
p_GeoDaWeight-class

p_GeoDaWeight
p_GeoDa-class

p_GeoDa
skater

Spatial C(K)luster Analysis by Tree Edge Removal
sp_to_geoda

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

A tabu-search algorithm to solve the max-p-region problem
mean_neighbors

Mean Neighbors of Spatial Weights
set_neighbors

Set neighbors of an observation
schc

Spatially Constrained Hierarchical Clucstering (SCHC)
summary.Weight

Summary of Spatial Weights
azp_tabu

A tabu algorithm to solve the AZP problem
as.matrix.Weight

spatial weights to matrix
LISA-class

LISA class (Internally Used)
azp_sa

A simulated annealing algorithm to solve the AZP problem
gda_queen_weights

(For internally use and test only) Queen Contiguity Spatial Weights
geoda-class

'geoda' class
gda_knn_weights

(For internally use and test only) K-Nearest Neighbors-based Spatial Weights
as.geoda

Create an instance of geoda-class from either an 'sf' or 'sp' object
create_weights

Create an empty weights
Weight-class

Weight class (Internally Used)
as.data.frame.geoda

convert rgeoda instance to data.frame
gda_rook_weights

(For internally use and test only) Rook Contiguity Spatial Weights
azp_greedy

A greedy algorithm to solve the AZP problem
geoda_open

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