Can someone help me on Sparse PCA? I am using the "elasticnet" package to perform sparse PCA. I am having a hard time in figuring out how many nonzero values should a component contain?
For example, In this code:
sparse.pca.result <- spca(X, K = 2, type = "predictor", sparse = "varnum", para = c(4, 4))
(para = c(4, 4)) indicates the number of non-zero components for each of the two PC’s respectively.
So the question is, how to identify the number of non-zero components?
I hope that someone could help me on this.