Stepwise Covariance-Free Common Principal Components (CF-CPC) With an Application to Neuroscience
Finding the common principal component (CPC) for ultra-high dimensional data is a multivariate technique used to discover the latent structure of covariance matrices of shared variables measured in two or more k conditions. Common eigenvectors are assumed for the covariance matrix of all conditions,...
Saved in:
Main Authors: | , , , |
---|---|
Format: | article |
Language: | EN |
Published: |
Frontiers Media S.A.
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/bdc035ecc71047b39a5c6301c4f74fc2 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|