Package: SpatPCA
Type: Package
Title: Regularized Principal Component Analysis for Spatial Data
Version: 1.2.0.1
Date: 2020-01-08
URL: https://github.com/egpivo/SpatPCA
BugReports: https://github.com/egpivo/SpatPCA/issues
Description: 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, <DOI:10.1080/10618600.2016.1157483>). The
  method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D.
License: GPL-3
Imports: Rcpp, RcppParallel
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
SystemRequirements: C++11
Author: Wen-Ting Wang, Hsin-Cheng Huang
Maintainer: Wen-Ting Wang <egpivo@gmail.com>
NeedsCompilation: yes
Packaged: 2020-01-08 13:54:37 UTC; wen-tingwang
Repository: CRAN
Date/Publication: 2020-01-09 14:00:05 UTC
Built: R 3.5.2; x86_64-apple-darwin15.6.0; 2020-01-11 11:01:12 UTC; unix
Archs: SpatPCA.so.dSYM
