English

On weighted approximations in $D[0, 1]$ with applications to self-normalized partial sum processes

Probability 2007-11-12 v1

Abstract

Let X,X1,X2,...X, X_1, X_2,... be a sequence of non-degenerate i.i.d. random variables with mean zero. The best possible weighted approximations are investigated in D[0,1]D[0, 1] for the partial sum processes {S[nt],0t1}\{S_{[nt]}, 0\le t\le 1\}, where Sn=j=1nXjS_n=\sum_{j=1}^nX_j, under the assumption that XX belongs to the domain of attraction of the normal law. The conclusions then are used to establish similar results for the sequence of self-normalized partial sum processes {S[nt]/Vn,0t1}\{S_{[nt]}/V_n, 0\le t\le 1\}, where Vn2=j=1nXj2V_n^2=\sum_{j=1}^nX_j^2. LpL_p approximations of self-normalized partial sum processes are also discussed.

Keywords

Cite

@article{arxiv.0711.1384,
  title  = {On weighted approximations in $D[0, 1]$ with applications to self-normalized partial sum processes},
  author = {Miklós Csörgő and Barbara Szyszkowicz and Qiying Wang},
  journal= {arXiv preprint arXiv:0711.1384},
  year   = {2007}
}

Comments

22 pages

R2 v1 2026-06-21T09:41:34.738Z