spnaf: Spatial Network Autocorrelation for Flow Data

Identify statistically significant flow clusters using the local spatial network autocorrelation statistic G_ij* proposed by 'Berglund' and 'Karlström' (1999) <doi:10.1007/s101090050013>. The metric, an extended statistic of 'Getis/Ord' G ('Getis' and 'Ord' 1992) <doi:10.1111/j.1538-4632.1992.tb00261.x>, detects a group of flows having similar traits in terms of directionality. You provide OD data and the associated polygon to get results with several parameters, some of which are defined by spdep package.

Version: 0.2.0
Depends: R (≥ 3.5.0)
Imports: dplyr, magrittr, sf, spdep, tidyr, rlang, rmarkdown, tmap
Suggests: knitr
Published: 2022-08-07
Author: Youngbin Lee ORCID iD [aut, cre], Hui Jeong Ha ORCID iD [aut], Sohyun Park ORCID iD [aut], Kyusik Kim ORCID iD [aut], Jinhyung Lee ORCID iD [aut]
Maintainer: Youngbin Lee <youngbin at snu.ac.kr>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: spnaf results


Reference manual: spnaf.pdf
Vignettes: Introduction to spnaf


Package source: spnaf_0.2.0.tar.gz
Windows binaries: r-devel: spnaf_0.2.0.zip, r-release: spnaf_0.2.0.zip, r-oldrel: spnaf_0.2.0.zip
macOS binaries: r-release (arm64): spnaf_0.2.0.tgz, r-oldrel (arm64): spnaf_0.2.0.tgz, r-release (x86_64): spnaf_0.2.0.tgz, r-oldrel (x86_64): spnaf_0.2.0.tgz
Old sources: spnaf archive


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