1
$\begingroup$

The following question was asked recently at https://mathoverflow.net/questions/326631/what-is-the-distribution-of-a-cartesian-power-of-a-collection-of-iid-uniform-poi :

Take a rectangle with positive volume $R\subset \mathbb{R}^d$ and form a set $S$ of $n$ points iid uniform over $R$. Take a Jordan-measurable region $U\subset R^k.$ What is $E\left[\left|U\cap S^k\right|\right]$?

The question has received a down vote and has just been deleted by its owner. I think the question makes sense and deserves to be answered, which is what I will try to do here.

$\endgroup$
1
  • $\begingroup$ Thanks for writing this, I assumed I received a downvote because the answer was so obvious. $\endgroup$ Nov 15, 2021 at 15:02

1 Answer 1

1
$\begingroup$

$\newcommand{\iii}{\mathbf i} \newcommand{\K}{\mathcal K}$ Quoting a comment by the OP of the quoted question:

I am seeking such an explicit expression, but have not been able to correctly perform all the combinatoral accounting required. Ideally the final expression should not involve a summation over elements of $S$, instead summing over a certain dimensional partitioning in the sense of my previous comment.

Let us provide such an expression (one may assume here, slightly more generally, that $U$ is Lebesgue measurable). With $[n]:=\{1,\dots,n\}$, we have \begin{equation*} |U\cap S^k|=\sum_{(i_1,\dots,i_k)\in[n]^k}1_{(X_{i_1},\dots,X_{i_k})\in U}, \end{equation*} where $X_1,\dots,X_n$ are iid points each uniformly distributed over the rectangle $R$ in $\mathbb R^d$. So, \begin{equation*} E|U\cap S^k|=\sum_{(i_1,\dots,i_k)\in[n]^k}P\big((X_{i_1},\dots,X_{i_k})\in U\big). \tag{1} \end{equation*} The probability $P\big((X_{i_1},\dots,X_{i_k})\in U\big)$ depends on $\iii:=(i_1,\dots,i_k)$ only through the partition \begin{equation*} \Pi(\iii):=\{J_1(\iii),\dots,J_n(\iii)\} \end{equation*} of the set $[k]$, where \begin{equation*} J_i(\iii):=\{j\in[k]\colon i_j=i\} \end{equation*} for $i\in[n]$. Take any such partition $\Pi(\iii)$ and clean it up by removing its empty elements and ordering the remaining, non-empty elements of it so that for the resulting ordered partition \begin{equation*} K=(K_1,\dots,K_s) \end{equation*} of the set $[k]$ we have the following: $s\in[k]$, the $K_\alpha$'s are pairwise disjoint, their union is $[k]$, and $\min K_\alpha<\min K_\beta$ whenever $1\le\alpha<\beta\le k$.

For any given $s\in[k]$, let $\K_s$ denote the set of all such ordered partitions $K$. Also let $K(\iii)$ denote the ordered partition in $\K_s$ (for some $s=s(\iii)\in[k]$ depending on $\iii$) obtained from the $k$-tuple $\iii$ by the just described procedure.

Then to restore any $k$-tuple $\iii$ given the corresponding ordered partition $K(\iii)$, we only need to "color" the $s$ members of the partition $K(\iii)$ by $s$ different "colors" selected from the $n$ available "colors" $1,\dots,n$; there are \begin{equation*} n_{(s)}:=n(n-1)\dots(n-(s-1)) \end{equation*} choices of such colorings of the given ordered partition $K=(K_1,\dots,K_s)$.

E.g., if $n=5$, $k=6$, and $\iii=(3,1,4,1,3,3)$, then only $s(\iii)=3$ different "colors" (namely, $1,3,4$) out of the $5$ available "colors" $1,\dots,5$ were actually used for this $\iii$, and the ordered partition $K(\iii)$ here is $K=(\{1,5,6\},\{2,4\},\{3\})$, where $\{1,5,6\}$ is the set of the positions of the $3$'s in this $\iii$, $\{2,4\}$ is the set of the positions of the $1$'s, and $\{3\}$ is the set of the positions of the $4$'s. The $k$-tuple $\iii=(3,1,4,1,3,3)$ is only one feasible coloring of this ordered partition $K=(\{1,5,6\},\{2,4\},\{3\})$; another feasible coloring is e.g. $(2,5,3,5,2,2)$.

However, given any such ordered partition $K\in\K_s$ with $s\in[k]$, the probability $P\big((X_{i_1},\dots,X_{i_k})\in U\big)$ will not further depend on the choice of $\iii=(i_1,\dots,i_k)$ with $K(\iii)=K$; this follows because the $X_i$'s are iid. In fact, for any such $K=(K_1,\dots,K_s)$ and any $\iii=(i_1,\dots,i_k)$ with $K(\iii)=K$ \begin{equation*} P\big((X_{i_1},\dots,X_{i_k})\in U\big)=P\big((Y_1(K),\dots,Y_k(K))\in U\big), \end{equation*} where \begin{equation*} Y_j(K):=X_\alpha\quad\text{if}\quad j\in K_\alpha \end{equation*} for some $\alpha\in[s]$.

Thus, by (1), \begin{equation*} E|U\cap S^k|=\sum_{s=1}^k n_{(s)} \sum_{K\in\K_s}P\big((Y_1(K),\dots,Y_k(K))\in U\big). \end{equation*}

In particular, if $U=T_1\times\cdots\times T_k$, where $T_1,\dots,T_k$ are Lebesgue-measurable subsets of rectangle $R$, then \begin{equation*} E|U\cap S^k|=\sum_{s=1}^k \frac{n_{(s)}}{\lambda_d(R)^s}\, \sum_{K\in\K_s}\prod_{\alpha=1}^s \lambda_d\Big(\bigcap_{j\in K_s}T_j\Big), \end{equation*} where $\lambda_d$ is the Lebesgue measure over $\mathbb R^d$.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.