gdverse - Analysis of Spatial Stratified Heterogeneity
Detecting spatial associations via spatial stratified heterogeneity, accounting for spatial dependencies, interpretability, complex interactions, and robust stratification. In addition, it supports the spatial stratified heterogeneity family described in Lv et al. (2025)<doi:10.1111/tgis.70032>.
Last updated
geodetectorgeographical-detectorgeoinformaticsgeospatial-analysisspatial-analysisspatial-data-analysisspatial-statisticsspatial-stratified-heterogeneitycpp
8.83 score 104 stars 2 dependents 34 scripts 714 downloadsspEDM - Spatial Empirical Dynamic Modeling
Inferring causation from spatial cross-sectional data through empirical dynamic modeling (EDM), with methodological extensions including geographical convergent cross mapping from Gao et al. (2023) <doi:10.1038/s41467-023-41619-6>, geographical cross mapping cardinality as introduced by Lyu et al. (2026) <doi:10.1080/13658816.2026.2687121>, as well as the spatial causality test following the approach of Herrera et al. (2016) <doi:10.1111/pirs.12144>, together with geographical pattern causality proposed in Zhang & Wang (2025) <doi:10.1080/13658816.2025.2581207>.
Last updated
causal-analysiscausal-discoverycausal-inferencecausal-influencecausal-interactionscausal-networkscppempirical-dynamic-modelinggeoinformaticsgeospatial-causalityspatial-analysisspatial-data-analysisspatial-data-sciencespatial-statisticsopenblascppopenmp
8.63 score 84 stars 42 scripts 629 downloadspc - Pattern Causality Analysis
Unveil interactions in complex systems through pattern causality analysis (PC), with the original algorithm for time series data by Stavroglou et al. (2020) <doi:10.1073/pnas.1918269117>, as well as methodological extensions for spatial cross-sectional data introduced by Zhang & Wang (2025) <doi:10.1080/13658816.2025.2581207>, together with a systematic description detailed in Lyu et al. (2026) <doi:10.1016/j.compenvurbsys.2026.102435>.
Last updated
causal-discoverycausal-interactionscausalitycausality-algorithmscausality-analysiscppcross-mappingdynamical-systemsempirical-dynamic-modelinggeoinformaticspattern-causalityspatial-data-analysisspatial-statisticstime-seriestime-series-analysiscpp
7.36 score 28 stars 136 scripts 438 downloadsinfoxtr - Information-Theoretic Measures for Revealing Variable Interactions
Implements information-theoretic measures to explore variable interactions, including KSG mutual information estimation for continuous variables from Kraskov et al. (2004) <doi:10.1103/PhysRevE.69.066138>, knockoff conditional mutual information described in Zhang & Chen (2025) <doi:10.1126/sciadv.adu6464>, synergistic-unique-redundant decomposition introduced by Martinez-Sanchez et al. (2024) <doi:10.1038/s41467-024-53373-4>, and information imbalance gain following Del Tatto et al. (2024) <doi:10.1073/pnas.2317256121>, allowing detection of complex and diverse relationships among variables.
Last updated
causal-discoverycausal-interactioncausalitycausality-analysiscppdata-driven-decision-makingdata-sciencegeoinformaticsinformaticsinformation-decompositioninformation-flowinformation-imbalanceinformation-theoryspatial-analysisspatial-data-sciencespatial-statisticsstatistical-inferencetime-series-analysiscpp
6.89 score 60 stars 478 downloadstEDM - Temporal Empirical Dynamic Modeling
Inferring causation from time series data through empirical dynamic modeling (EDM), with methods such as convergent cross mapping from Sugihara et al. (2012) <doi:10.1126/science.1227079>, partial cross mapping introduced by Leng et al. (2020) <doi:10.1038/s41467-020-16238-0>, and cross mapping cardinality described in Tao et al. (2023) <doi:10.1016/j.fmre.2023.01.007>, following a systematic description proposed in Lyu et al. (2026) <doi:10.1016/j.compenvurbsys.2026.102435>.
Last updated
causal-analysiscausal-discoverycausal-inferencechaoscppdynamical-systemsempirical-dynamic-modelingtemporal-causal-discoverytemporal-causalitytime-seriestime-series-analysisurban-analyticsurban-data-scienceopenblascppopenmp
6.64 score 79 stars 2 scripts 307 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 Lyu.
Last updated
geoinformaticsspatial-data-analysisspatial-data-sciencespatial-statisticsopenblascpp
6.19 score 31 stars 11 dependents 6 scripts 787 downloadsinfocausality - Information-Theoretic Measure of Causality
Methods for quantifying temporal and spatial causality through information flow, and decomposing it into unique, redundant, and synergistic components, following the framework described in Martinez-Sanchez et al. (2024) <doi:10.1038/s41467-024-53373-4>.
Last updated
causal-discoverycausalityentropy-measuresinfo-theoryinformation-flowtemporal-causalitytime-series-analysiscpp
5.26 score 9 stars 291 downloadscoupling - Analysis of Coupling Coordination Degree
Implements coupling coordination degree (CCD) models and supports metacoupling analysis following Tang et al. (2021) <doi:10.1016/j.scs.2021.103405>.
Last updated
couplingcoupling-analysiscoupling-coordination-degreeintracouplingmeta-couplingmetacouplingpericouplingspatial-analysisspatial-data-analysisspatial-data-sciencetelecouplingcpp
5.23 score 17 stars 341 downloads
cisp - A Correlation Indicator Based on Spatial Patterns
Utilizes spatial association marginal contributions derived from spatial stratified heterogeneity to capture the degree of correlation between spatial patterns.
Last updated
associationcorrelationgeoinformaticssimilarity-measurementspatial-patterns
5.18 score 10 stars 2 scripts 318 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
cpp
5.11 score 13 stars 296 downloads
geocn - Loads Spatial Data Sets of China
Providing various commonly used spatial data related to Chinese regions in the R programming environment.
Last updated
chinachina-regiongeospatial-visualizationmaps
4.38 score 24 stars 7 scripts
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
geoinformaticsgeospatial-analysisinformation-theoryspatial-statisticsspatial-stratified-heterogeneitycpp
4.54 score 7 stars 2 scripts 230 downloads