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SpatPCA  

Regularized Principal Component Analysis for Spatial Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("SpatPCA", "1.3.8")



Attach the package and use:
library("SpatPCA")
Maintained by
Wen-Ting Wang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-01-23
Latest Update: 2023-11-13
Description:
Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigen-functions by using the alternating direction method of multipliers algorithm (Wang and Huang, 2017, <doi:10.1080/10618600.2016.1157483>). The method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D.
How to cite:
Wen-Ting Wang (2015). SpatPCA: Regularized Principal Component Analysis for Spatial Data. R package version 1.3.8, https://cran.r-project.org/web/packages/SpatPCA. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:26), 1.0.0.1 (2015-02-06 08:32), 1.0.0.2 (2015-06-06 07:50), 1.0 (2015-01-23 09:06), 1.1.0.0 (2015-11-01 17:53), 1.1.1.0 (2016-02-11 08:27), 1.1.1.1 (2016-05-27 10:45), 1.1.1.2 (2017-03-18 01:20), 1.2.0.0 (2018-02-20 23:44), 1.2.0.1 (2020-01-09 15:00), 1.3.3.0 (2021-01-31 16:30), 1.3.5 (2023-11-13 10:33)
Other packages that cited SpatPCA R package
View SpatPCA citation profile
Other R packages that SpatPCA depends, imports, suggests or enhances
Complete documentation for SpatPCA
Functions, R codes and Examples using the SpatPCA R package
Full SpatPCA package functions and examples
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