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Consider $n$ iid real-valued random vectors of size $k$ having iidcoordinates with a general distribution function $F$. A vector is a maximum ifand only if there is no other vector in the sample which weakly dominates it inall coordinates. Let $p_{k,n}$ be the probability that the first vector is amaximum. The main result of the present paper is that if $k\equiv k_n$ isgrowing at a slower (faster) rate than a certain factor of $\log(n)$, then$p_{k,n} \rightarrow 0$ (resp. $p_{k,n}\rightarrow1$) as $n\to\infty$.Furthermore, the factor is fully characterized as a functional of $F$. We alsostudy the effect of $F$ on $p_{k,n}$, showing that while $p_{k,n}$ may behighly affected by the choice of $F$, the phase transition is the same for alldistribution functions up to a constant factor.

A phase transition for the probability of being a maximum among random vectors with general iid coordinates