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Consider the following sets: $$ A = \Big\{ x\in X: \Pr\bigg(\lim_{n \to \infty}d\big(p_n, [\ell(x), u(x) ] \big)= 0\bigg)=1 \Big\}, $$ and $$ A_n = \Big\{ x\in X: d\big(p_n, [\ell(x), u(x) ] \big)= 0\Big\}, $$ where:

  • $\Pr$ denotes probability.
  • $X\subseteq \mathbb{R}$.
  • $(p_n)_n$ is a sequence of random variables taking values in $[0,1]$.
  • $\ell(\cdot)$ and $u(\cdot)$ are real function taking values in $[0,1]$.
  • $d\big(p_n, [\ell(x), u(x) ] \big):= \inf \big\{|p_n - y| : y \in [\ell(x), u(x) ] \big\}$.

Could you help me to show that $$ d_H(A, A_n)\rightarrow_{a.s.} 0, $$ where $$ d_H(A, A_n)\equiv \max\{\sup_{x\in A_n}d(x,A), \sup_{x\in A}d(x, A_n)\}, $$ is the Hausdorff distance.

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2 Answers 2

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$\newcommand\de\delta\newcommand\ep\varepsilon$You wrote

Could you help me to show that under Ass1 and Ass2 $$d_H(A, A_n)\rightarrow_{a.s.} 0$$

Of course, this is not true in such generality. For instance, suppose that $X=[0,1)$, $\ell(x)=u(x)=x(1-x)$ for $x\in X$, and $p_n=u(\ep_n)$, where $\ep_n:=\sqrt{(\ln2)/(2n)}$.

Then $$A_n=\{x\in X\colon p_n=u(x)\}=\{\ep_n,1-\ep_n\},$$ $$A=\{x\in X\colon p_n\to u(x)\}=\{0\}\ne\emptyset,$$ $$A_n(\de)=\{x\in X\colon|p_n-u(x)|\le\de\}.$$ So, for each $x\in A$ and each real $\de>0$ we have $x=0$ and hence $$\Pr(x\in A_n(\de))=\Pr(0\in A_n(\de))=\Pr(|p_n|\le\de) \\ =\Pr(p_n\le\de)\ge\Pr(\ep_n\le\de)=1(\ep_n\le\de) \\ =1(\sqrt{(\ln2)/(2n)}\le\de)\ge1-\frac{2}{\exp(2n\de^2)}.$$

So, all your assumptions hold. However, $$d_H(A,A_n)\to1\ne0.$$

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    $\begingroup$ @Star : Yes, I think any additional questions should be posted elsewhere. However, it is clear that the continuity of $\ell$ and $u$ cannot help, as they are continuous in my example. On the other hand, $\ell$ and $u$ are not bijective in my example. So, you may want to think in that direction. $\endgroup$ Commented Feb 27 at 15:07
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    $\begingroup$ @Star : Please post additional questions in separate posts. $\endgroup$ Commented Feb 28 at 14:49
  • $\begingroup$ I have bene thinking a lot about this problem and I believe that I was considering the wrong objects. So, I have moved my focus to some slightly different sets. If possible, could yo take a look at my new question here mathoverflow.net/questions/467446/show-convergence-of-sets $\endgroup$
    – Star
    Commented Mar 21 at 12:30
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EDIT: That whole answer assumes the $p_n$'s are uniformly and independently distributed on $[0,1]$. I have no idea on how to extend it to the general case of other distributions.

It gets elementary after you look at $A$ in simple cases. For example when $\ell(x) = 0$ and $u(x) = \frac{1}{2}$ for all $x$ and the $p_n$'s are uniformly and independently distributed on $[0,1]$. Then almost surely both $p_n\in[0,\frac{1}{2}]$ for infinitely many $n$'s and $p_n\in[\frac{3}{4},1]$ for infinitely many other $n$'s. Therefore $d\big(p_n, [0, \frac{1}{2}]\big)$ keeps oscillating too widely and $$a := \lim_{n \to \infty}d\big(p_n, [\ell(x), u(x) ]\big)$$ almost surely doesn't exist and $A$ is almost always empty in that special case of functions.

Now let's go back to the general case of any real functions $\ell()$ and $u()$. With the same reasonning, $a$ almost surely doesn't exist for any $x$ with $0 < \ell(x)$ or $u(x) < 1$. Conversely, $a$ is always $0$ for any $x$ with $\ell(x) \le 0$ and $1 \le u(x)$. Therefore $$ A = \{ x\in X: \ell(x) \le 0 < 1 \le u(x)\} $$ and trivially $$A\subseteq A_n\quad \forall n.$$

EDIT: This proves (2) is true iff $\ell(x) \le 0 < 1 \le u(x)$ for some $x\in X$.

(1) and (3) are false when for example $X=[0,1]$ and $\ell(x) = 0$ on $[0,\frac{1}{2}]$, $\ell(x)=\frac{3}{4}$ on $(\frac{1}{2}, 1]$ and $u(x) = 1$ on $[0,1]$. Because then $A = [0,\frac{1}{2}]$ and $A_n$ almost surely contains $\frac{3}{4}$ for infinitely many $n$'s hence $d_H(A,A_n)>\frac{1}{4}$ infinitely often and cannot go to zero.

Along these lines, you should have no trouble showing (1) and (3) hold if the functions $\ell()$ and $u()$ are continuous on $X$, $\ell(x) \le 0 < 1 \le u(x)$ for some $x\in X$ and $\ell(x) > 0$ for some other $x\in X$.

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    $\begingroup$ Thanks Claude. Why is it complicated to show the general case? In my question, I am assuming that $A$ is non-empty, so the limit above exists for at least one $x$. $\endgroup$
    – Star
    Commented Feb 16 at 9:33
  • $\begingroup$ The same reasoning also works whenever $(p_n)$ almost surely doesn't converge. @GoldenRetrieverLover's answer seems to address the other extreme case when $(p_n)$ almost surely converge (I wish I could undo my downvote). Now what happens if the probability space is a mixture in between? $\endgroup$ Commented Feb 16 at 9:48
  • $\begingroup$ Thanks. Could you revise your answer based on that? Also, I cannot assume that $(p_n)$ almost surely converges. This is indeed why this question is difficult. $\endgroup$
    – Star
    Commented Feb 16 at 10:38

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