Package: geosimilarity
Title: Geographically Optimal Similarity
Version: 3.9
Authors@R: 
    c(
      person(given = "Yongze", family = "Song",
             email = "yongze.song@outlook.com", 
             role = c("aut", "cph"),
             comment = c(ORCID = "0000-0003-3420-9622")),
      person(given = "Wenbo", family = "Lyu",
             email = "lyu.geosocial@gmail.com", 
             role = c("aut", "cre"),
             comment = c(ORCID = "0009-0002-6003-3800"))
     )
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) 
             <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. 
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.3
URL: https://github.com/ausgis/geosimilarity,
        https://ausgis.github.io/geosimilarity/
BugReports: https://github.com/ausgis/geosimilarity/issues
Depends: R (>= 4.1.0)
Imports: stats, parallel, tibble, dplyr (>= 1.1.0), purrr, ggplot2,
        magrittr, ggrepel
Suggests: cowplot, viridis, car, DescTools, PerformanceAnalytics,
        testthat (>= 3.0.0), sdsfun, rmarkdown, knitr
LazyData: true
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-03-27 04:47:40 UTC; 31809
Author: Yongze Song [aut, cph] (ORCID: <https://orcid.org/0000-0003-3420-9622>),
  Wenbo Lyu [aut, cre] (ORCID: <https://orcid.org/0009-0002-6003-3800>)
Maintainer: Wenbo Lyu <lyu.geosocial@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-27 15:50:02 UTC
Built: R 4.6.0; ; 2026-04-26 13:12:21 UTC; unix
