Weak convergence of self-normalized partial sums processes

preprint2013arXivOpen access

Abstract

Let {X,Xn,n≥1}\{X, X_n, n\geq 1\} be a sequence of independent identically distributed non-degenerate random variables. Put S0=0,Sn=∑i=1nXiS_0=0, S_n = \sum^n_{i=1} X_i and Vn2=∑i=1nXi2,n≥1.V_n^2=\sum^n_{i=1} X_i^2, n\ge 1. A weak convergence theorem is established for the self-normalized partial sums processes {S[nt]/Vn,0≤t≤1}\{S_{[nt]}/V_n, 0\le t\le 1\} when XX belongs to the domain of attraction of a stable law with index α∈(0,2]α\in (0,2]. The respective limiting distributions of the random variables max⁡1≤i≤n∣Xi∣/Sn{\max_{1\le i\le n}|X_i|}/{S_n} and max⁡1≤i≤n∣Xi∣/Vn{\max_{1\le i\le n}|X_i|}/{V_n} are also obtained under the same condition.

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