Principal Component Analysis - Software/source Code

Software/source Code

  • In the NAG Library, principal components analysis is implemented via the g03aa routine (available in both the Fortran and the C versions of the Library).
  • In the MATLAB Statistics Toolbox, the functions princomp and pca (R2012b) give the principal components, while the function pcares gives the residuals and reconstructed matrix for a low-rank PCA approximation. An example MATLAB implementation of PCA is available.
  • in Octave, a free software computational environment mostly compatible with MATLAB, the function princomp gives the principal component.
  • in the free statistical package R, the functions princomp and prcomp can be used for principal component analysis; prcomp uses singular value decomposition which generally gives better numerical accuracy. Recently there has been an explosion in implementations of principal component analysis in various R packages, generally in packages for specific purposes.
  • in SAS, PROC FACTOR offers principal components analysis.
  • In XLMiner, the Principal Components tab can be used for principal component analysis.
  • In Stata, the pca command provides principal components analysis.
  • Cornell Spectrum Imager - An open-source toolset built on ImageJ. Enables quick easy PCA analysis for 3D datacubes.
  • imDEV - Free Excel addin to calculate principal components using R package
  • "ViSta: The Visual Statistics System" - a free software that provides principal components analysis, simple and multiple correspondence analysis.
  • "Spectramap" - software to create a biplot using principal components analysis, correspondence analysis or spectral map analysis.
  • FinMath - a .NET numerical library containing an implementation of PCA.
  • The Unscrambler is a multivariate analysis software enabling Principal Component Analysis (PCA) with PCA Projection.
  • Computer Vision Library
  • NMath, a proprietary numerical library containing PCA for the .NET Framework.
  • In IDL, the principal components can be calculated using the function pcomp.
  • Weka computes principal components.
  • Software for analyzing multivariate data with instant response using PCA
  • Orange (software) supports PCA through its Linear Projection widget.
  • A version of PCA adapted for population genetics analysis can be found in the suite EIGENSOFT.
  • PCA can also be performed by the statistical software Partek Genomics Suite.

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