Timeline for Solving for auto-regression coefficients when covariance is singular?
Current License: CC BY-SA 4.0
3 events
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| Jun 20, 2022 at 21:01 | comment | added | Aksakal | Ledoit wolf shrinks to a certain kind of a matrix. You can use the idea to shrink to something else, if you have a better target matrix. For instance, you could use a diagonal matrix or scaled identity matrix | |
| Jun 20, 2022 at 20:09 | comment | added | Yaroslav Bulatov |
Thanks for the idea! I actually get much better results by replacing LedoitWolf with ShrunkCovariance, updated question with link to code. Both of them are worse than just numerically inverting the singular covariance matrix and sticking the result into formula -- formula divides by diagonal, so the resulting coefs become reasonable. This is a general problem with regularization, optimal lambda is problem specific, hard to check for correctness
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| Jun 20, 2022 at 18:50 | history | answered | Aksakal | CC BY-SA 4.0 |