Principal component analysis and its generalizations for any type of sequence (PCA-Seq)

Principal component analysis and its generalizations for any type of sequence (PCA-Seq)

In the 1940s, Karhunen and Loève proposed a method for processing a one-dimensional numeric time series by converting it into multidimensional by shifts. In fact, a one-dimensional number series was decomposed into several orthogonal time series. This method has many times been independently develop...

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Bibliographic Details
Main Authors:	V. M. Efimov, K. V. Efimov, V. Y. Kovaleva
Format:	Article
Language:	English
Published:	Siberian Branch of the Russian Academy of Sciences, Federal Research Center Institute of Cytology and Genetics, The Vavilov Society of Geneticists and Breeders 2020-01-01
Series:	Вавиловский журнал генетики и селекции
Subjects:	time series svd pca pco mds ssa molecular sequences p-distance
Online Access:	https://vavilov.elpub.ru/jour/article/view/2395

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