Comments (3)
@Banana1530 , is this fully addressed by #29 or is there more to do? (The only thing I can think is to allow more / arbitrary weight schemes, but I don't know if that's actually useful.)
If there's nothing more to do, we can close this and #27.
from moma.
Let's close this issue. In my experience sparse PCA with SLOPE, LASSO, SCAD or MCP are basically the same.
from moma.
Sounds good - certainly for the SPCA case they should be essentially equivalent. (The sub-problems are linear regression with an identity matrix, which pretty much any method should be able to get right.) In theory, they might differ more for a case with a weird smoothing matrix, but most of the smoothers used in practice are pretty well-behaved as well.
from moma.
Related Issues (20)
- End-to-End Tests
- Skip RNG Set-Up
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from moma.