Package: spnaf 1.1.0

Youngbin Lee

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.

Authors:Youngbin Lee [aut, cre], Hui Jeong Ha [aut], Sohyun Park [aut], Kyusik Kim [aut], Jinhyung Lee [aut]

spnaf_1.1.0.tar.gz
spnaf_1.1.0.tar.gz(r-4.5-noble)spnaf_1.1.0.tar.gz(r-4.4-noble)
spnaf_1.1.0.tgz(r-4.4-emscripten)spnaf_1.1.0.tgz(r-4.3-emscripten)
spnaf.pdf |spnaf.html
spnaf/json (API)

# Install 'spnaf' in R:
install.packages('spnaf', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • CA - Sample migration data by counties in California.
  • CA_polygon - Sample polygon data of California counties.

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.18 score 2 scripts 175 downloads 2 exports 39 dependencies

Last updated 5 months agofrom:5aa246f65d. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 26 2024
R-4.5-linuxOKNov 26 2024

Exports:Gij.flowNetworknb

Dependencies:bootclassclassIntclicpp11DBIdeldirdplyre1071fansigenericsglueKernSmoothlatticelifecyclemagrittrMASSpillarpkgconfigproxypurrrR6Rcpprlangs2sfspspDataspdepstringistringrtibbletidyrtidyselectunitsutf8vctrswithrwk

Introduction to spnaf

Rendered fromIntroduction_to_spnaf.Rmdusingknitr::rmarkdownon Nov 26 2024.

Last update: 2024-06-13
Started: 2022-03-23