Timeline for How to simulate a path through its solution and conditional expectation / variance
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Apr 18, 2018 at 13:34 | vote | accept | SinusK | ||
| Apr 16, 2018 at 13:23 | answer | added | phdstudent | timeline score: 0 | |
| Apr 15, 2018 at 13:18 | comment | added | SinusK | Yes it is Gaussian. You can determine each x(t) for all t since you know it is normally distributed and its mean and variance are known. But how to simulate the path with each point x(0), x(1), x(2) ,.......???? | |
| Apr 13, 2018 at 17:05 | review | Close votes | |||
| Apr 17, 2018 at 15:40 | |||||
| Apr 13, 2018 at 16:46 | comment | added | Quantuple | You have everything you need since in that case the stochastic integral is Gaussian due to the deterministic nature of the integrand. I'm voting to close this question as it is too basic (look for 'Ornstein Uhlembeck' process simulation) | |
| Apr 12, 2018 at 21:56 | history | asked | SinusK | CC BY-SA 3.0 |