Timeline for Calculating the probability of an event defined by a condition on a Gaussian random process
Current License: CC BY-SA 3.0
4 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Nov 10, 2013 at 6:34 | vote | accept | Mehmet Ozan Kabak | ||
| Jul 13, 2012 at 1:46 | comment | added | cardinal | @Mehmet: In the answer I posted, you get the same form for the bound with quantitative information on the constants, if the process has mean zero and is stationary. The (second) constant $C$ in Nate's answer implicitly depends on $T$, as you note. | |
| Jul 12, 2012 at 14:46 | comment | added | Mehmet Ozan Kabak | Thanks for the answer and also pointing me to this nice resource. Intuitively one would expect the probability to be an increasing function of $T = |t_2 - t_1|$ and a decreasing function of $K$. The result you quoted definitely confirms the second intuition. However I don't see any explicit reference to $T$ there; it is absorbed in the constants. It is a very important parameter in my application and I need to express the dependence on it more explicitly. | |
| Jul 8, 2012 at 0:57 | history | answered | Nate Eldredge | CC BY-SA 3.0 |