Timeline for Perturbation results for statistical estimators
Current License: CC BY-SA 4.0
9 events
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Mar 5 at 7:43 | comment | added | Alex M. | @YemonChoi: If it were not for the clumsy formulation "by the likes of researchers like", this answer is so generic that I would believe it to be AI-generated. Sadly, with a score of 2, it is impossible to flag it as VLQ anymore, and I have exhausted my NaN flag. Maybe you could flag it as NaN yourself, assuming that you have not exhausted that option, like me? | |
Mar 4 at 21:27 | comment | added | Yemon Choi | @AlexM. While I had similar impressions I thought I would give the writer of the answer the chance to explain themselves. | |
Mar 4 at 11:13 | comment | added | Alex M. | For future reviewers, the question is: "are there any sufficient conditions on $f$ and the estimator that I use, such that I can bound the difference between $\hat{f}$ and $\tilde{f}$ (measured in, say, the $L_1$ sense), as a function of the perturbations $\epsilon_i$? Are there any general theorems of this kind that talk about how sensitive an estimator distribution is to perturbations of the samples?" | |
Mar 4 at 11:10 | comment | added | Alex M. | @YemonChoi: Guess what? I have flagged this post as NaN, but "a moderator reviewed your flag, but found no evidence to support it", so it got declined. With 3 undeserved upvotes (!), it will be very difficult now to delete this non-answer... And a message to future readers: when you review answers, always remember to check them against the questions that they claim to answer. In this particular case, there is almost no connection between the question and the answer. | |
Mar 4 at 7:17 | comment | added | Yemon Choi | Could you clarify how these rather generic statements apply to the particular question "are there any sufficient conditions on $f$ and the estimator that I use, such that ..." | |
Mar 3 at 21:55 | review | Low quality posts | |||
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Mar 3 at 21:46 | review | Late answers | |||
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S Mar 3 at 21:30 | review | First answers | |||
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S Mar 3 at 21:30 | history | answered | Datageek | CC BY-SA 4.0 |