show/hide this revision's text 3 Fixed some bad indexing.

You're right that things change for m>1; I was thinking sloppily.

Assume $U=\{1,\ldots,n\}$ for concreteness. If $Y_1,\ldots,Y_m$ are chosen independently and uniformly from $U$, then for any $k_1,\ldots,k_m\in U$, we of course have $$ \Pr[Y_1=k_1,\ldots,Y_m=k_m] = \frac{1}{n^m}. $$

On the other hand, if $x=(x_1,\ldots,x_m)$ is chosen uniformly from the standard $n$-simplex and $Y_1,\ldots,Y_m$ are then chosen independently according to $x$, then $$ \Pr[Y_1=k_1,\ldots,Y_m=k_m] = \mathbb{E}\Pr[Y_1=k_1,\ldots,Y_m=k_m|x] = \mathbb{E}\prod_{i=1}^m x_{k_i} = \frac{n!}{(n+r)!}\prod_{j=1}^m frac{n!}{(n+r)!}\prod_{j=1}^n r_j!, $$ where $r_j = \#\{i\in U #\{1\le i \le m : k_i=j\}$ and $r=r_1 + \cdots r_m$r_n$. This last expectation can be proved most easily from Lemma 1 in this paper.

    Post Undeleted by Mark Meckes
show/hide this revision's text 2 Rewrote, now hopefully a correct answer.

I'll assume that the answer to the question in my comment above is "yes", so

You're right that we can assume m=1things change for m>1; I was thinking sloppily.

Assume also for simplicity that $U=\{1,\ldots,n\}$ for concreteness.

As in Michael's comment, let's denote by $x=(x_1,\ldots, x_n)$ a uniform random point in the standard If $n$-simplex, Y_1,\ldots,Y_m$ are chosen independently and denote by $Y$ the number uniformly from $U$ chosen according to U$, then for any $x$. Then k_1,\ldots,k_m\in U$, we of course have the conditional probability $\Pr[Y=i|x $ \Pr[Y_1=k_1,\ldots,Y_m=k_m] = x_i]$\frac{1}{n^m}. $$

On the other hand, if $x=(x_1,\ldots,x_m)$ is chosen uniformly from the standard $n$-simplex and so $Y_1,\ldots,Y_m$ are then chosen independently according to $x$, then $$ \Pr[Y=i] = Pr[Y_1=k_1,\ldots,Y_m=k_m] = \mathbb{E} \Pr[Y=i|x] mathbb{E}\Pr[Y_1=k_1,\ldots,Y_m=k_m|x] = \mathbb{E} x_i mathbb{E}\prod_{i=1}^m x_{k_i} = \frac{1}{n}\sum_{j=1}^n \mathbb{E} x_j =\frac{1}{n}. frac{n!}{(n+r)!}\prod_{j=1}^m r_j!, $$

So where $Y$ does indeed have the uniform distribution on r_j = \#\{i\in U : k_i=j\}$ and $U$.r=r_1 + \cdots r_m$. This last expectation can be proved most easily from Lemma 1 in this paper.

    Post Deleted by Mark Meckes
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