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First of all, I'm sorry if this question makes no sense for this package. I am back to studying PCA, and I have a lot of (potentially disconnected) information in my head.
I performed a PCA using prcomp() from base R. In one of the tutorials I read online, the number of PCs was decided based on the eigenvalues. When using prcomp(), I can simply use the get_eigenvalue() from the "factoextra" package, then I have access to the eigenvalues, variance.percent, and cumulative.variance.percent.
In the PCAtools package, there are other functions and plots for defining the number of PCs, which is super awesome. However, I still wanted to take a look at the eigenvalues. The get_eigenvalue() from factoextra doesn't seem to work. Is there any alternative? I tried looking the the pca object but couldn't see any number matching prcomp() values.
Best,
Luiz
The text was updated successfully, but these errors were encountered:
First of all, I'm sorry if this question makes no sense for this package. I am back to studying PCA, and I have a lot of (potentially disconnected) information in my head.
I performed a PCA using
prcomp()
from base R. In one of the tutorials I read online, the number of PCs was decided based on the eigenvalues. When usingprcomp()
, I can simply use theget_eigenvalue()
from the "factoextra" package, then I have access to the eigenvalues, variance.percent, and cumulative.variance.percent.In the PCAtools package, there are other functions and plots for defining the number of PCs, which is super awesome. However, I still wanted to take a look at the eigenvalues. The
get_eigenvalue()
from factoextra doesn't seem to work. Is there any alternative? I tried looking the the pca object but couldn't see any number matchingprcomp()
values.Best,
Luiz
The text was updated successfully, but these errors were encountered: