SecDim: The Second Dimension of Spatial Association

Most of the current methods explore spatial association using observations at sample locations, which are defined as the first dimension of spatial association (FDA). The proposed concept of the second dimension of spatial association (SDA), as described in Yongze Song (2022) <doi:10.1016/j.jag.2022.102834>, aims to extract in-depth information about the geographical environment from locations outside sample locations for exploring spatial association.

Version: 3.2
Depends: R (≥ 4.1.0)
Imports: stats, RcppArmadillo, methods, geosphere
Suggests: knitr, rmarkdown
Published: 2023-05-20
DOI: 10.32614/CRAN.package.SecDim
Author: Yongze Song ORCID iD [aut, cre]
Maintainer: Yongze Song < at>
License: GPL-2
NeedsCompilation: no
CRAN checks: SecDim results


Reference manual: SecDim.pdf
Vignettes: 'SecDim' Package for The Second Dimension of Spatial Association


Package source: SecDim_3.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SecDim_3.2.tgz, r-oldrel (arm64): SecDim_3.2.tgz, r-release (x86_64): SecDim_3.2.tgz, r-oldrel (x86_64): SecDim_3.2.tgz
Old sources: SecDim archive

Reverse dependencies:

Reverse imports: geosimilarity


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