Package: geosimilarity 3.7
Wenbo Lv
geosimilarity: Geographically Optimal Similarity
Understanding spatial association is essential for spatial statistical inference, including factor exploration and spatial prediction. Geographically optimal similarity (GOS) model is an effective method for spatial prediction, as described in Yongze Song (2022) <doi:10.1007/s11004-022-10036-8>. GOS was developed based on the geographical similarity principle, as described in Axing Zhu (2018) <doi:10.1080/19475683.2018.1534890>. GOS has advantages in more accurate spatial prediction using fewer samples and critically reduced prediction uncertainty.
Authors:
geosimilarity_3.7.tar.gz
geosimilarity_3.7.tar.gz(r-4.5-noble)geosimilarity_3.7.tar.gz(r-4.4-noble)
geosimilarity_3.7.tgz(r-4.4-emscripten)geosimilarity_3.7.tgz(r-4.3-emscripten)
geosimilarity.pdf |geosimilarity.html✨
geosimilarity/json (API)
NEWS
| # Install 'geosimilarity' in R: |
| install.packages('geosimilarity', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ausgis/geosimilarity/issues
Last updated 6 days agofrom:eeaaddeb64. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 18 2024 |
| R-4.5-linux | OK | Oct 18 2024 |
Exports:%>%gosgos_bestkapparemoveoutlier
Dependencies:clicolorspacedplyrfansifarvergenericsggplot2ggrepelgluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpurrrR6RColorBrewerRcpprlangscalestibbletidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| geographically optimal similarity | gos |
| function for the best kappa parameter | gos_bestkappa |
| Spatial grid data of explanatory variables. | grid |
| Removing outliers. | removeoutlier |
| Spatial datasets of trace element Zn. | zn |
