English

A CLT for weighted time-dependent uniform empirical processes

Probability 2014-12-30 v1

Abstract

For a uniform process {Xt:tE}\{ X_t: t\in E\} (by which XtX_t is uniformly distributed on (0,1)(0,1) for tEt\in E) and a function w(x)>0w(x)>0 on (0,1)(0,1), we give a sufficient condition for the weak convergence of the empirical process based on {w(x)(1Xtxx):tE,x[0,1]}\{ w(x)(\mathbb{1}_{X_t\leq x} -x): t\in E, x\in [0,1]\} in (E×[0,1])\ell^\infty(E\times [0,1]). When specializing to w(x)1w(x)\equiv 1 and assuming strict monotonicity on the marginal distribution functions of the input process, we recover a result of Kuelbs, Kurtz, and Zinn (2013). In the last section, we give an example of the main theorem.

Keywords

Cite

@article{arxiv.1412.8162,
  title  = {A CLT for weighted time-dependent uniform empirical processes},
  author = {Yuping Yang},
  journal= {arXiv preprint arXiv:1412.8162},
  year   = {2014}
}
R2 v1 2026-06-22T07:45:08.631Z