Timeline for Simulating a stochastic integral
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
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| Feb 26, 2019 at 22:30 | review | Close votes | |||
| Feb 28, 2019 at 15:13 | |||||
| Feb 26, 2019 at 21:39 | answer | added | user186735 | timeline score: -2 | |
| Dec 20, 2017 at 20:46 | answer | added | user186735 | timeline score: 0 | |
| Mar 3, 2016 at 17:04 | answer | added | Yves | timeline score: 4 | |
| Mar 3, 2016 at 16:20 | history | tweeted | twitter.com/StackStats/status/705427730075090944 | ||
| Mar 3, 2016 at 6:46 | comment | added | Yves |
The program does what it should, although it can be made both simpler and more efficient: use a cumsum in place of the i loop. Matrix/apply could also be preferred here to data frame/sapply, etc. This is a very good exercise. Hints: state clearly what you expect to find and why, find the joint distribution of the $n$ summed variables say $X_i$.
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| Mar 3, 2016 at 0:07 | answer | added | Glen_b | timeline score: 4 | |
| Mar 2, 2016 at 19:50 | comment | added | Evan Aad | @GregPetersen: I don't expect to see exactly $0.5$, but I do expect to see consistent convergence to $0.5$, e.g. $0.4771895, 0.4804475 0.5160542 0.4964552$. | |
| Mar 2, 2016 at 17:58 | comment | added | Greg Petersen | Have you calculated the variance at each n? You will never get exactly 0.5 so what you will need to do is determine if you can reject your null hypothesis of being at 0.5. | |
| Mar 2, 2016 at 17:22 | history | asked | Evan Aad | CC BY-SA 3.0 |