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SpatPCA Package

Description

SpatPCA is an R package designed for efficient regularized principal component analysis, providing the following features:

Identification of dominant spatial patterns (eigenfunctions) with both smooth and localized characteristics.
Spatial prediction (Kriging) at new locations.
Adaptability for regularly or irregularly spaced data, spanning 1D, 2D, and 3D datasets.
Implementation using the alternating direction method of multipliers (ADMM) algorithm.

Installation

To install the current development version from GitHub, use the following R code:

remotes::install_github("egpivo/SpatPCA")

For compiling C++ code with the required RcppArmadillo and RcppParallel packages, follow these instructions:

Windows users: Install Rtools
Mac users: Install Xcode Command Line Tools, and install the gfortran library. You can achieve this by running the following commands in the terminal:

brew update
brew install gcc

For a detailed solution, refer to this link, or download and install the library gfortran to resolve the error ld: library not found for -lgfortran.

Usage

library(SpatPCA)
spatpca(position, realizations)

Input: Realizations with the corresponding positions.
Output: Return the most dominant eigenfunctions automatically.
For more details, refer to the Demo.

Author

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.