Timeline for Generating causally dependent random variables
Current License: CC BY-SA 3.0
5 events
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Oct 17, 2013 at 8:09 | comment | added | AsymLabs | At the very least, as indicated in the equation above, this would not be a stationary effect. I would think that a first step would be to bin the readings according to time interval and then compare them. I don't know how many readings you have but this comparison could be run through something like Pearson's Distribution as a starting point - to try to classify the nature of the distribution. | |
Oct 17, 2013 at 7:50 | comment | added | sebastian | I think my problem is rather clear - I have the measured distribution of $\bf{v}$ and $\bf{a}$ and from this I'd like to sample a pseudo-random $\bf{v_{rand}}$, that ultimately reproduces the input. I'm well aware of your point on whether what comes out of it is realistic, but that's a different question... | |
Oct 16, 2013 at 20:42 | history | edited | AsymLabs | CC BY-SA 3.0 |
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Oct 16, 2013 at 20:23 | history | edited | AsymLabs | CC BY-SA 3.0 |
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Oct 16, 2013 at 20:14 | history | answered | AsymLabs | CC BY-SA 3.0 |