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fastLISA  

Fast Local Indicators of Spatial Association (LISA)
View on CRAN: Click here


Download and install fastLISA package within the R console
Install from CRAN:
install.packages("fastLISA")

Install from Github:
library("remotes")
install_github("cran/fastLISA")

Install by package version:
library("remotes")
install_version("fastLISA", "1.0.1")



Attach the package and use:
library("fastLISA")
Maintained by
Lizhong Chen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-20
Latest Update: 2026-07-20
Description:
Computes various Local Indicators of Spatial Association (LISA) statistics, including univariate and bivariate local Moran's I, Empirical Bayes local Moran's I, univariate and multivariate local Geary's C, and Getis-Ord G and G* statistics. The methods follow Anselin (1995), Getis and Ord (1992), and Anselin (2019). Leverages a high-performance, plain-C backend with optional OpenMP multi-core support for fast permutation-based pseudo-p-value calculation. Accepts any 'spdep' listw spatial weight matrix, including custom and non-contiguity weights. Uses sample standardisation (n-1) and 'rgeoda'-style permutation p-values. Output cluster codes match 'rgeoda' conventions, including the Isolated category for observations without neighbours.
How to cite:
Lizhong Chen (2026). fastLISA: Fast Local Indicators of Spatial Association (LISA). R package version 1.0.1, https://cran.r-project.org/web/packages/fastLISA. Accessed 03 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:37), 1.0.0 (2026-07-06 16:30)
Other packages that cited fastLISA R package
View fastLISA citation profile
Other R packages that fastLISA depends, imports, suggests or enhances
Complete documentation for fastLISA
Functions, R codes and Examples using the fastLISA R package
Full fastLISA package functions and examples
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Maintainer: Lu Mao (view profile)

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