English

Nonparametric sequential prediction for stationary processes

Probability 2011-04-11 v1

Abstract

We study the problem of finding an universal estimation scheme hn:RnRh_n:\mathbb{R}^n\to \mathbb{R}, n=1,2,...n=1,2,... which will satisfy \lim_{t\rightarrow\infty}{\frac{1}{t}}\sum_{i=1}^t|h_ i(X_0,X_1,...,X_{i-1})-E(X_i|X_0,X_1,...,X_{i-1})|^p=0 a.s. for all real valued stationary and ergodic processes that are in LpL^p. We will construct a single such scheme for all 1<p1<p\le\infty, and show that for p=1p=1 mere integrability does not suffice but Llog+LL\log^+L does.

Keywords

Cite

@article{arxiv.1104.1555,
  title  = {Nonparametric sequential prediction for stationary processes},
  author = {Gusztáv Morvai and Benjamin Weiss},
  journal= {arXiv preprint arXiv:1104.1555},
  year   = {2011}
}

Comments

Published in at http://dx.doi.org/10.1214/10-AOP576 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org)

R2 v1 2026-06-21T17:51:19.550Z