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The colour scale in the structures represents the position along each principal component going between the extremes, from red to green to blue.
Fig. 3 Variance corresponding to each principal component.
where is the eigenvalue of each principal component.
The amount of variance explained by each principal component is shown in brackets.
Each principal component is a linear combination of the original variables.
This coefficient indicates how much each principal component contributes to the representation of the given attribute.
PC1 and PC2 represented 35.4 and 34.1 % of the variance explained by each principal component, respectively.
Each principal component is then interpreted, and the function best representing a sediment flux pattern is chosen from these components.
The corresponding alpha level for each principal component reflects how consistently the variables measure the principal component.
The amplitude of the variance of principal components can be regarded as the amount of information in each principal component.
(4) Decompose the covariance matrix using principal component analysis (11) where is the eigenvalue of each principal component.
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