Description Usage Arguments Value Author(s) References Examples
The RCC_PCA criterion is a new tool to determine the optimal number of components (i.e. PCs) to retain for Principal Component Analysis (PCA). This criterion balances between the following two desires, reducing the dimension of the data and increasing the accuracy of the final results of PCA; See Alshammri (2021).
1 | RCC_PCA(x)
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x |
a N-by-m data matrix, where the rows are "N" observations, and the columns are "m" variables |
The values of RCC criterion
Fayed Alshammri
Alshammri, F. (2021). Retained component criterion for optimizing principal component analysis. Manuscript submitted for publication.
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