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nipals (version 1.0)

Principal Components Analysis using NIPALS or Weighted EMPCA, with Gram-Schmidt Orthogonalization

Description

Principal Components Analysis of a matrix using Non-linear Iterative Partial Least Squares or weighted Expectation Maximization PCA with Gram-Schmidt orthogonalization of the scores and loadings. Optimized for speed. See Andrecut (2009) .

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Version

Install

install.packages('nipals')

Monthly Downloads

812

Version

1.0

License

MIT + file LICENSE

Maintainer

Kevin Wright

Last Published

December 2nd, 2024

Functions in nipals (1.0)

empca

Principal component analysis by weighted EMPCA, expectation maximization principal component-analysis
avg_angular_distance

Average angular distance between two rotation matrices
nipals

Principal component analysis by NIPALS, non-linear iterative partial least squares
uscrime

U.S. Crime rates per 100,00 people