Reduced-rank approximations to spectroscopic and compositional data: A universal framework based on log-ratios and counting statistics

Published 2015 View Full Article

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Title
Reduced-rank approximations to spectroscopic and compositional data: A universal framework based on log-ratios and counting statistics
Authors
Keywords
Maximum likelihood principal component analysis (MLPCA), Centred log-ratio (clr) transformation, Compositional data, Poisson distribution, Multinomial distribution, Error propagation, Denoising
Journal
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
Volume 142, Issue -, Pages 206-218
Publisher
Elsevier BV
Online
2015-02-08
DOI
10.1016/j.chemolab.2015.02.001

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