Strong confidence intervals for autoregression
Statistics Theory
2011-11-10 v1 Methodology
Statistics Theory
Abstract
In this short note I apply the methodology of game-theoretic probability to calculating non-asymptotic confidence intervals for the coefficient of a simple first order scalar autoregressive model. The most distinctive feature of the proposed procedure is that with high probability it produces confidence intervals that always cover the true parameter value when applied sequentially.
Cite
@article{arxiv.0707.0660,
title = {Strong confidence intervals for autoregression},
author = {Vladimir Vovk},
journal= {arXiv preprint arXiv:0707.0660},
year = {2011}
}
Comments
7 pages, 2 tables, 2 figures