Suppose real-valued random variables $\{X_{n}\} $ converges to $X$ in distribution. Then, will the quantile of the distribution of $\{X_n\}$ converge to the quantile of $X$? .
Asked
Active
Viewed 4,851 times
1 Answers
7
Yes. If $X$ is a random variable with distribution function $F$, then for $0<p<1$ define the quantile function as $Q(p)=\inf(x: F(x)\geq p)$. Then $X_n\to X$ in distribution if and only if $Q_n(p)\to Q(p)$ at all continuity points $p$ of $Q$.
Added: It's a nice exercise to prove this result from the definition. On the other hand, it is Proposition 5 (page 250) in A Modern Approach to Probability Theory by Bert Fristedt and Lawrence Gray, and is also proved in Chapter 21 of Asymptotic Statistics by A. W. van der Vaart.
-
But what if $Q$ is not continuous at $p$? – webster Dec 25 '11 at 11:09
-
Suppose we know that $F$ is strictly increasing. Will this additional condition help? – webster Dec 25 '11 at 14:08
-
The discontinuity points of $Q$ correspond to the "flat spots" on the graph of $F$ (Draw a picture!). So if $F$ is strictly increasing, then $Q$ is continuous at all $0<p<1$. – Dec 25 '11 at 15:26
-
Yes. But what will be the formal proof? – webster Dec 25 '11 at 16:25
-
By the way, if $F$ is strictly increasing on the support of $X$, and the supports of all $X_n$ are contained in the support of $X$, then $Q$ is continuous on $[0,1]$, and the convergence of the quantile functions is uniform. This simple observation has applications in the theory of Toeplitz matrices. http://dx.doi.org/10.1007/s40590-016-0105-y – Egor Maximenko Oct 23 '16 at 03:04
-
I don't think the cited Proposition 5 in Fristedt & Gray has anything to do with quantiles, although it does have the letter Q; it starts, "Let Q and Qn, n=1,2,..., be probability measures..." and says nothing about quantiles. (The point of the proposition is conditions for sequence of rv Xn to converge a.s. to rv X, instead of just convergence in distribution.) – David M Kaplan Jul 04 '22 at 17:13
-
The references are not convincing. – Snoop Dec 14 '22 at 08:26