gdverse - Analysis of Spatial Stratified Heterogeneity
Analyzing spatial factors and exploring spatial associations based on the concept of spatial stratified heterogeneity, while also taking into account local spatial dependencies, spatial interpretability, complex spatial interactions, and robust spatial stratification. Additionally, it supports the spatial stratified heterogeneity family established in academic literature.
Last updated 2 days ago
geographical-detectorgeoinformaticsgeospatial-analysisspatial-statisticsspatial-stratified-heterogeneitycpp
8.69 score 32 stars 1 dependents 41 scripts 405 downloads
sdsfun - Spatial Data Science Complementary Features
Wrapping and supplementing commonly used functions in the R ecosystem related to spatial data science, while serving as a basis for other packages maintained by Wenbo Lv.
Last updated 3 days ago
geoinformaticsspatial-data-analysisspatial-data-sciencespatial-statisticsopenblascppopenmp
6.53 score 15 stars 8 dependents 6 scripts 415 downloads
spEDM - Spatial Empirical Dynamic Modeling
Analyze causality in geospatial data using empirical dynamic modeling (EDM) through geographical convergent cross mapping (GCCM) by Gao et al. (2023) <doi:10.1038/s41467-023-41619-6> and multispatial convergent cross mapping (multispatialCCM) by Clark et al. (2015) <doi:10.1890/14-1479.1>.
Last updated 2 days ago
causal-inferencecppempirical-dynamic-modelinggeoinformaticsgeospatial-causalityspatial-statisticscpp
5.54 score 10 stars 2 scripts 345 downloads
sesp - Spatially Explicit Stratified Power
Assesses spatial associations between variables through an equivalent geographical detector (q-statistic) within a regression framework and incorporates a spatially explicit stratified power model by integrating spatial dependence and spatial stratified heterogeneity, facilitating the modeling of complex spatial relationships.
Last updated 7 days ago
spatial-explicit-geographical-detectorspatial-stratified-heterogeneitycpp
5.43 score 15 stars 4 scripts
geocn - Loads Spatial Data Sets of China
Providing various commonly used spatial data related to Chinese regions in the R programming environment.
Last updated 1 months ago
chinachina-regiongeospatial-visualizationmaps
4.85 score 14 stars 10 scripts
cisp - A Correlation Indicator Based on Spatial Patterns
Use the spatial association marginal contributions derived from spatial stratified heterogeneity to capture the degree of correlation between spatial patterns.
Last updated 1 months ago
associationcorrelationgeoinformaticsspatial-patternspatial-stratified-heterogeneity
4.60 score 2 stars 2 scripts 466 downloads
sshicm - Information Consistency-Based Measures for Spatial Stratified Heterogeneity
Spatial stratified heterogeneity (SSH) denotes the coexistence of within-strata homogeneity and between-strata heterogeneity. Information consistency-based methods provide a rigorous approach to quantify SSH and evaluate its role in spatial processes, grounded in principles of geographical stratification and information theory (Bai, H. et al. (2023) <doi:10.1080/24694452.2023.2223700>; Wang, J. et al. (2024) <doi:10.1080/24694452.2023.2289982>).
Last updated 30 days ago
geoinformaticsgeospatial-analysisinformation-theoryspatial-statisticsspatial-stratified-heterogeneitycpp
4.48 score 2 stars 2 scripts 157 downloads
itmsa - Information-Theoretic Measures for Spatial Association
Leveraging information-theoretic measures like mutual information and v-measure to quantify spatial associations between patterns (Nowosad and Stepinski (2018) <doi:10.1080/13658816.2018.1511794>; Bai, H. et al. (2023) <doi:10.1080/24694452.2023.2223700>).
Last updated 24 days ago
cpp
3.30 score 1 stars
itmsa - Information-Theoretic Measures for Spatial Association
Leveraging information-theoretic measures like mutual information and v-measure to quantify spatial associations between patterns (Nowosad and Stepinski (2018) <doi:10.1080/13658816.2018.1511794>; Bai, H. et al. (2023) <doi:10.1080/24694452.2023.2223700>).
Last updated 24 days ago
cpp
3.00 score