# Does the uniform distribution minimize the expected value in the coupon collector's problem?

Stanley Yu 07/11/2018. 3 answers, 155 views

Given a discrete probability distribution with $n$ possible outcomes and the task of repeatedly sampling until getting each outcome at least once, does the uniform distribution give the smallest expected value for the total number of samples?

Clement C. 07/11/2018.

Yes. This is shown e.g. in [1], under the name Collector's inequality:

The result we wish to point out is that $A(\mathbf{p})$ is a Schur-convex function of the probability vector $\mathbf{p}$. That is, if $\mathbf{p} \gg \mathbf{q}$, then $A(\mathbf{p}) > A(\mathbf{q})$. Thus, the minimum value of $A(\mathbf{p})$ occurs when $\mathbf{p}$ is the uniform distribution $\mathbf{u} = (1/n,\dots,1/n)$.

[1] Clevenson, M. Lawrence, and William Watkins. Majorization and the Birthday Inequality. Mathematics Magazine, vol. 64, no. 3, 1991, pp. 183–188. JSTOR, JSTOR, www.jstor.org/stable/2691301.

saulspatz 07/11/2018.

In the paper "Birthday paradox, coupon collectors, caching algorithms and self-organizing search" equation $(13b)$ gives the expected number of draws to get a complete collection of $m$ coupons, where coupon $i$ has probability $p_i$ as $$\int_0^{\infty}\left(1-\prod_{i=1}^m(1-e^{-p_it})\right)\mathrm{dt}$$ Clearly it is enough to show that for every $t\ge0,$the maximum value of $\prod_{i=1}^m(1-e^{-p_it}),$ subject to $0\le p_i,\ i=1,\dots,m$ and $\sum_{i=1}^mp_i=1,$ occurs when all the $p_i=1/m.$ This is easy; take the logarithm of the product and use Lagrange multipliers.

joriki 07/11/2018.

Ignore all but two of the coupon types. Conditional on the combined number $n$ of coupons of these two types having been drawn, the probability that both types have been drawn is $1-p^n-(1-p)^n$, where $p$ is the probability that a coupon of one of these two types is of the first type. This is maximal for $p=\frac12$. Thus a distribution is only optimal if $p=\frac12$ for all pairs of types, that is, if it is uniform.