Timeline for Behavior of the sum of the exponents of chi-squared random variables normalized by their maximum
Current License: CC BY-SA 3.0
7 events
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| Apr 13, 2017 at 12:58 | history | edited | CommunityBot |
replaced http://mathoverflow.net/ with https://mathoverflow.net/
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| Oct 30, 2013 at 5:48 | comment | added | ofer zeitouni | Well, it is still similar. Just estimate how many points there are at distance $x$ behind the expected location of the maximum. The first moment estimate will give the correct answer. The details depend of course on the function $g$. | |
| Oct 30, 2013 at 2:56 | history | edited | Bullmoose | CC BY-SA 3.0 |
grammar
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| Oct 30, 2013 at 2:54 | comment | added | Bullmoose | @oferzeitouni I substantially revised this question. While the work I did on it is based on your answer to one of my previous question, I think it's now dissimilar from this question. If you have any ideas about what do here, please share. Thanks! | |
| Oct 30, 2013 at 2:47 | history | edited | Bullmoose | CC BY-SA 3.0 |
massive changes to the question; original question asked was not correct
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| Sep 30, 2013 at 10:43 | comment | added | ofer zeitouni | Well, it is the same question really as your related question mathoverflow.net/questions/142772/… (except that I misread it then and thus my answer was wrong - now corrected). Your $S(n)$ will converge to $0$ because actually most of the sequence is FAR from the maximum in the relevant scale). To see that, use the same estimate that by now you should understand on the probability that a single variable is near the expected location of the maximum, and apply asymptotics for a binomial variable with that $p$. | |
| Sep 30, 2013 at 2:58 | history | asked | Bullmoose | CC BY-SA 3.0 |