English

Central limit theorem under variance uncertainty

Probability 2015-08-31 v2

Abstract

We prove the central limit theorem (CLT) for a sequence of independent zero-mean random variables ξj\xi_j, perturbed by predictable multiplicative factors λj\lambda_j with values in intervals [λj,λj][\underline\lambda_j,\overline\lambda_j]. It is assumed that the sequences λj\underline\lambda_j, λj\overline\lambda_j are bounded and satisfy some stabilization condition. Under the classical Lindeberg condition we show that the CLT limit, corresponding to a "worst" sequence λj\lambda_j, is described by the solution vv of one-dimensional GG-heat equation. The main part of the proof follows Peng's approach to the CLT under sublinear expectations, and utilizes H\"{o}lder regularity properties of vv. Under the lack of such properties, we use the technique of half-relaxed limits from the theory of viscosity solutions.

Keywords

Cite

@article{arxiv.1506.01551,
  title  = {Central limit theorem under variance uncertainty},
  author = {Dmitry B. Rokhlin},
  journal= {arXiv preprint arXiv:1506.01551},
  year   = {2015}
}

Comments

11 pages

R2 v1 2026-06-22T09:47:14.947Z