Timeline for Probabilty to have y balls in bin A if N balls where distributed in X bins
Current License: CC BY-SA 4.0
4 events
| when toggle format | what | by | license | comment | |
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| Jun 7, 2018 at 17:23 | comment | added | deasmhumnha | Of course, the selection events must be i.i.d. as well for the joint to be multinomial. | |
| Jun 7, 2018 at 17:16 | comment | added | deasmhumnha | If you assume a generating model of selecting one bin (with replacement) and placing a single ball into said bin, and repeat, the distribution is clearly multinomial. This is probably what people intuitively think when they say random assignment. Now there are certainly other assignment models (pick a Poisson number of bins, assign based on Dirichlet probabilities, etc.) that are not multinomial, but will require changing the bin selection framework significantly, as any sequential random selection (any discrete distribution over boxes) with replacement will produce a multinomial distribution. | |
| Jun 7, 2018 at 13:19 | comment | added | whuber♦ | Could you clarify that initial phrase about "equal or unequal"? It seems to me that some forms of unequal assignment probabilities will produce decidedly non-multinomial distributions, depending on what you mean by "assignment probability." | |
| Jun 7, 2018 at 4:30 | history | answered | deasmhumnha | CC BY-SA 4.0 |