Timeline for Intuition of the "work" done by random variables in Monte Carlo methods (incl. MCL)
Current License: CC BY-SA 4.0
9 events
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| Dec 28, 2021 at 9:58 | comment | added | Carlo Beenakker | "uncertainty" is the root-mean-square deviation = square root of the variance; the variance increases linearly with the number $N$ of (independent) iterations, hence the $\sqrt N$ increase of the uncertainty | |
| Dec 28, 2021 at 9:23 | comment | added | litmus | Ok, this is really helpful, thanks! I have looked at Signal-to-Noise in wiki but cant understand how uncertainty is increased by sqrt(N). Does this relation have a specific name? Any article or term you would recommend where I can use to find more info? | |
| Dec 27, 2021 at 14:43 | history | edited | Carlo Beenakker | CC BY-SA 4.0 |
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| Dec 27, 2021 at 14:31 | comment | added | Carlo Beenakker | micro and macro effects work together: both the macro effect (the signal) and the micro effect (the noise) increase with each iteration; what matters is that the signal-to-noise ratio goes up. | |
| Dec 27, 2021 at 14:29 | history | edited | Carlo Beenakker | CC BY-SA 4.0 |
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| Dec 27, 2021 at 13:59 | comment | added | litmus | I edited my main question to hopefully make it less vague. Your answer helped, but I am looking at understanding on a micro level (the work/effect of each random variable) rather than the aggregated macro level (averages / LLN).. | |
| Dec 27, 2021 at 13:39 | comment | added | litmus | Thanks! But what is the case for my question, is it a false or true statement that random variables act as a "tool/mechanism" for us to be able to create multiple iterations (to measure and average) of an otherwise deterministic experiment? | |
| Dec 27, 2021 at 13:25 | vote | accept | litmus | ||
| Dec 27, 2021 at 11:03 | history | answered | Carlo Beenakker | CC BY-SA 4.0 |