Spectral PCA for MANOVA and data over binary trees
Journal Title
Journal of Multivariate Analysis
Abstract
We extend a concept of ANOVA broader than the traditional variance component models to MANOVA. Within this framework we can derive a spectral principal component analysis (PCA) and see how it generalises the same notion for weakly stationary vector time series. We then attempt to obtain analogous results for arrays of random variables over (i.e., indexed by the nodes of) binary trees, with only partial success. While there is an analogue of ANOVA and MANOVA for binary trees, the existence of spectral PCA there is unresolved.
Keywords
ANOVA; MANOVA; PCA; Spectral PCA
Research Division(s)
Bioinformatics
Terms of Use/Rights Notice
Refer to copyright notice on published article.


Creation Date: 2022-02-18 04:40:37
Last Modified: 2022-02-18 04:40:56
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