Abstract

The empirical mean of nn independent and identically distributed (i.i.d.) random variables (X1,…,Xn)(X_1,\dots,X_n) can be viewed as a suitably normalized scalar projection of the nn-dimensional random vector X(n)≐(X1,…,Xn)X^{(n)}\doteq(X_1,\dots,X_n) in the direction of the unit vector n−1/2(1,1,…,1)∈Sn−1n^{-1/2}(1,1,\dots,1) \in \mathbb{S}^{n-1}. The large deviation principle (LDP) for such projections as n→∞n\rightarrow\infty is given by the classical Cramér's theorem. We prove an LDP for the sequence of normalized scalar projections of X(n)X^{(n)} in the direction of a generic unit vector θ(n)∈Sn−1θ^{(n)} \in \mathbb{S}^{n-1}, as n→∞n\rightarrow\infty. This LDP holds under fairly general conditions on the distribution of X1X_1, and for "almost every" sequence of directions (θ(n))n∈N(θ^{(n)})_{n\in\mathbb{N}}. The associated rate function is "universal" in the sense that it does not depend on the particular sequence of directions. Moreover, under mild additional conditions on the law of X1X_1, we show that the universal rate function differs from the Cramér rate function, thus showing that the sequence of directions n−1/2(1,1,…,1)∈Sn−1,n^{-1/2}(1,1,\dots,1) \in \mathbb{S}^{n-1}, n∈Nn \in \mathbb{N}, corresponding to Cramér's theorem is atypical.

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