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Self-normalized Cram\'{e}r type moderate deviations for the maximum of sums

Abstract

Let X1,X2,...X_1,X_2,... be independent random variables with zero means and finite variances, and let Sn=βˆ‘i=1nXiS_n=\sum_{i=1}^nX_i and Vn2=βˆ‘i=1nXi2V^2_n=\sum_{i=1}^nX^2_i. A Cram\'{e}r type moderate deviation for the maximum of the self-normalized sums max⁑1≀k≀nSk/Vn\max_{1\leq k\leq n}S_k/V_n is obtained. In particular, for identically distributed X1,X2,...,X_1,X_2,..., it is proved that P(max⁑1≀k≀nSkβ‰₯xVn)/(1βˆ’Ξ¦(x))β†’2P(\max_{1\leq k\leq n}S_k\geq xV_n)/(1-\Phi (x))\rightarrow2 uniformly for 0<x≀o(n1/6)0<x\leq\mathrm{o}(n^{1/6}) under the optimal finite third moment of X1X_1.Comment: Published in at http://dx.doi.org/10.3150/12-BEJ415 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

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