Timeline for Tail bounds for random Gaussian chaos?
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 20, 2021 at 3:42 | comment | added | jlewk | The last part of the abstract of arxiv.org/abs/1912.10754 suggests the paper will have some answers to these issues, and possibly answers to your question. | |
| Oct 20, 2021 at 3:38 | comment | added | jlewk | Absolute continuity is not suficient. If $d=1$ and $n\in\{1,2\}$ then $E[(\chi^2_n)^{-1}]=+\infty$. | |
| Oct 20, 2021 at 2:23 | history | edited | Drew Brady | CC BY-SA 4.0 |
added 1 character in body
|
| Oct 20, 2021 at 2:17 | history | edited | Drew Brady | CC BY-SA 4.0 |
added 136 characters in body
|
| Oct 20, 2021 at 2:15 | comment | added | Drew Brady | But even somewhat mild conditions would prevent that from being true (e.g. $x_j$ has law absolutely continuous w.r.t. Lebesgue measure). This question makes sense, provided we assume that $\mathbb{E}_x[\mathrm{Tr}(\Sigma^{-1})]$ exists and is finite? | |
| Oct 20, 2021 at 1:27 | comment | added | jlewk | What is the distribution of the $x_j$? If $P(x_j=0)>0$ then $E_x[trace\Sigma^{-1}]$ is $+\infty$. | |
| Oct 16, 2021 at 7:59 | history | asked | Drew Brady | CC BY-SA 4.0 |