Timeline for Probability distribution & Interpretation
Current License: CC BY-SA 4.0
7 events
when toggle format | what | by | license | comment | |
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Jan 26, 2022 at 18:37 | vote | accept | Suriya Kumar J S | ||
Jan 25, 2022 at 16:07 | comment | added | Glen_b | That works if F and G are continuous; but this doesn't break up a big spike of probability into smaller ones (you can't convert a geometric with mean 0.25 into a Poisson with mean 10, for example) | |
Jan 25, 2022 at 10:08 | answer | added | Tim | timeline score: 3 | |
Jan 25, 2022 at 9:14 | comment | added | Xi'an | Mathematically, the transform of $X\sim F$ into $Y\sim G$ can always be obtained by $$Y=G^{-1}(F(X))$$ | |
Jan 25, 2022 at 8:18 | comment | added | Suriya Kumar J S | My intention is to know, why so much obsession over gaussian, and why not other distribution. Then, I know we can use box-cox transform to convert any unknown distribution to normal, is there any other transform to convert a Poisson-like distribution to an actual Poisson distribution | |
Jan 25, 2022 at 7:59 | comment | added | Tim | What is the problem you are trying to solve? Why do you bother about it being a Poisson distribution? | |
Jan 25, 2022 at 7:19 | history | asked | Suriya Kumar J S | CC BY-SA 4.0 |