Package: GD 10.3

Yongze Song

GD: Geographical Detectors for Assessing Spatial Factors

Geographical detectors for measuring spatial stratified heterogeneity, as described in Jinfeng Wang (2010) <doi:10.1080/13658810802443457> and Jinfeng Wang (2016) <doi:10.1016/j.ecolind.2016.02.052>. Includes the optimal discretization of continuous data, four primary functions of geographical detectors, comparison of size effects of spatial unit and the visualizations of results. To use the package and to refer the descriptions of the package, methods and case datasets, please cite Yongze Song (2020) <doi:10.1080/15481603.2020.1760434>. The model has been applied in factor exploration of road performance and multi-scale spatial segmentation for network data, as described in Yongze Song (2018) <doi:10.3390/rs10111696> and Yongze Song (2020) <doi:10.1109/TITS.2020.3001193>, respectively.

Authors:Yongze Song [aut, cre]

GD_10.3.tar.gz
GD_10.3.tar.gz(r-4.5-noble)GD_10.3.tar.gz(r-4.4-noble)
GD_10.3.tgz(r-4.4-emscripten)GD_10.3.tgz(r-4.3-emscripten)
GD.pdf |GD.html
GD/json (API)

# Install 'GD' in R:
install.packages('GD', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • h1n1_100 - Spatial datasets of H1N1 flu incidences
  • h1n1_150 - Spatial datasets of H1N1 flu incidences
  • h1n1_50 - Spatial datasets of H1N1 flu incidences
  • ndvi_10 - Spatial datasets of vegetation index changes.
  • ndvi_20 - Spatial datasets of vegetation index changes.
  • ndvi_30 - Spatial datasets of vegetation index changes.
  • ndvi_40 - Spatial datasets of vegetation index changes.
  • ndvi_5 - Spatial datasets of vegetation index changes.
  • ndvi_50 - Spatial datasets of vegetation index changes.

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

10 exports 4 stars 5.01 score 11 dependencies 1 dependents 55 mentions 46 scripts 1.6k downloads

Last updated 1 years agofrom:87367aa08e. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-linuxOKSep 13 2024

Exports:discgdgdecogdinteractgdmgdriskoptidiscriskmeansesuv2m

Dependencies:apeBAMMtoolsbitopscaToolsdigestgplotsgtoolsKernSmoothlatticenlmeRcpp

Optimal Parameters-based Geographical Detectors (OPGD) Model for Spatial Heterogeneity Analysis and Factor Exploration

Rendered fromGD.Rmdusingknitr::rmarkdownon Sep 13 2024.

Last update: 2023-09-18
Started: 2018-05-15