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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 |
| Author: |
Yongze Song  [aut,
cre] |
| Maintainer: |
Yongze Song <yongze.song at outlook.com> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| CRAN checks: |
SecDim results |
Documentation:
Downloads:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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