Published online by Cambridge University Press: 15 July 2020
Let V be an n-set, and let X be a random variable taking values in the power-set of V. Suppose we are given a sequence of random coupons
$X_1, X_2, \ldots $
, where the
$X_i$
are independent random variables with distribution given by X. The covering time T is the smallest integer
$t\geq 0$
such that
$\bigcup_{i=1}^t X_i=V$
. The distribution of T is important in many applications in combinatorial probability, and has been extensively studied. However the literature has focused almost exclusively on the case where X is assumed to be symmetric and/or uniform in some way.
In this paper we study the covering time for much more general random variables X; we give general criteria for T being sharply concentrated around its mean, precise tools to estimate that mean, as well as examples where T fails to be concentrated and when structural properties in the distribution of X allow for a very different behaviour of T relative to the symmetric/uniform case.