See kkdey.github.io.
My parts of this web site are licensed under CC BY.
R package for adaptive correlation and covariance matrix shrinkage.
License: GNU General Public License v3.0
See kkdey.github.io.
My parts of this web site are licensed under CC BY.
What would be the best way to parallelise it, or incorporate parallelisation? Are there any plans to parallelise CorShrink?
Hi Kushal - This is a really great method. I had a couple questions regarding the different options available:
For Spearman correlations, can I input the rho and n into the CorShrinkVector()
function, or do rank correlations require bootstrapped-derived SEs for valid inference?
I have a large number of correlations, but I am only interested in positive correlations. This will also save computational time because it is A LOT of correlations. If I subset to only positive correlations and feed them into CorShrinkVector()
, would specifying the "+uniform" distribution be the best way to proceed?
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