SpatPCA (

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Regularized Principal Component Analysis for Spatial Data.

Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigenfunctions by using the alternating direction method of multipliers algorithm (Wang and Huang, 2017, ). The method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D.

Maintainer: Wen-Ting Wang
Author(s): Wen-Ting Wang, Hsin-Cheng Huang

License: GPL-3

Uses: Rcpp, RcppParallel

Released 17 days ago.

8 previous versions



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