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geosimilarity  

Geographically Optimal Similarity
View on CRAN: Click here


Download and install geosimilarity package within the R console
Install from CRAN:
install.packages("geosimilarity")

Install from Github:
library("remotes")
install_github("cran/geosimilarity")

Install by package version:
library("remotes")
install_version("geosimilarity", "3.9")



Attach the package and use:
library("geosimilarity")
Maintained by
Wenbo Lv
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-05-17
Latest Update: 2024-10-17
Description:
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) . GOS was developed based on the geographical similarity principle, as described in Axing Zhu (2018) . GOS has advantages in more accurate spatial prediction using fewer samples and critically reduced prediction uncertainty.
How to cite:
Wenbo Lv (2022). geosimilarity: Geographically Optimal Similarity. R package version 3.9, https://cran.r-project.org/web/packages/geosimilarity. Accessed 12 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:42), 1.1 (2022-05-17 18:20), 2.2 (2022-11-08 17:00), 3.0 (2024-08-21 13:40), 3.1 (2024-08-29 10:00), 3.2 (2024-09-08 17:10), 3.3 (2024-09-15 06:00), 3.6 (2024-09-29 09:50), 3.7 (2024-10-17 18:50), 3.8 (2025-09-23 04:20)
Other packages that cited geosimilarity R package
View geosimilarity citation profile
Other R packages that geosimilarity depends, imports, suggests or enhances
Complete documentation for geosimilarity
Functions, R codes and Examples using the geosimilarity R package
Some associated functions: bestkappa . gos . grid . zn . 
Some associated R codes: bestkappa.R . data.R . gos.R . zzz.R .  Full geosimilarity package functions and examples
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