Timeline for Tight upper-bound on dependent events
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jun 4, 2022 at 2:45 | comment | added | lchen | I have accepted your answer:) | |
| Jun 4, 2022 at 2:44 | vote | accept | lchen | ||
| Jun 2, 2022 at 3:29 | comment | added | lchen | My comment was not clear. What I meant is that if $(c_{ij})$ is sparse (having many zero elements), $E_i$ and $E_j$ can be correlated, and we may hope to have some result. But I now see that it is still highly intractable. | |
| Jun 1, 2022 at 13:39 | comment | added | Iosif Pinelis | '"overlap" on only a single $x_k$": What do you mean by that? It is generally not a good idea to denote a random variable and its values by the same symbol -- this creates confusion. | |
| Jun 1, 2022 at 13:11 | comment | added | lchen | Thank you Losif for your comment and pointing out the reference. I now see that the problem is intuitively understandable but hard to solve. My original thought is: suppose two events $E_i$ and $E_j$ "overlap" on only a single $x_k$ where $c_{ik}$ and $c_{jk}$ are non-zero; I was expecting results like $\Pr(E_i\cup E_j)\le a\cdot[\Pr(E_i)+ \Pr(E_j)]$ with some $a<1$. | |
| May 31, 2022 at 13:31 | history | answered | Iosif Pinelis | CC BY-SA 4.0 |