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All Projects → egpivo → SpatPCA

egpivo / SpatPCA

Licence: other
R Package: Regularized Principal Component Analysis for Spatial Data

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pcasplinesspatial-datar-packagercpparmadillocovariance-estimationrcppparallel

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SpatPCA Package

R build status Coverage Status

Description

SpatPCA is an R package that facilitates regularized principal component analysis,

  • seeking the dominant patterns (eigenfunctions), which can be smooth and localized
  • computing spatial prediction (Kriging) at new locations
  • suitable for either regularly or irregularly spaced data, including 1D, 2D, and 3D
  • by the alternating direction method of multipliers (ADMM) algorithm

Installation

To get the current development version from GitHub:

devtools::install_github("egpivo/SpatPCA")

To compile C++ code with the package RcppArmadillo,

  • Windows users require Rtools
  • Mac users require Xcode Command Line Tools, and install the library gfortran by typing the following lines into terminal
brew update
brew install gcc

More details can be found here.

Usage

library(SpatPCA)
spatpca(position, realizations)
  • Input: realizations with the corresponding position
  • Output: return the most dominant eigenfunctions automatically.
  • More details can be referred to Demo

Author

Wen-Ting Wang and Hsin-Cheng Huang

Maintainer

Wen-Ting Wang

Reference

Wang, W.-T. and Huang, H.-C. (2017). Regularized principal component analysis for spatial data. Journal of Computational and Graphical Statistics, 26, 14-25.

License

GPL-3

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