Sequential Estimation Methods from Inclusion Principle
Statistics Theory
2013-11-05 v1 Machine Learning
Probability
Statistics Theory
Abstract
In this paper, we propose new sequential estimation methods based on inclusion principle. The main idea is to reformulate the estimation problems as constructing sequential random intervals and use confidence sequences to control the associated coverage probabilities. In contrast to existing asymptotic sequential methods, our estimation procedures rigorously guarantee the pre-specified levels of confidence.
Cite
@article{arxiv.1208.1056,
title = {Sequential Estimation Methods from Inclusion Principle},
author = {Xinjia Chen},
journal= {arXiv preprint arXiv:1208.1056},
year = {2013}
}
Comments
28 pages, no figure; in proceedings of SPIE conference, Baltimore, Maryland, April 24-27, 2012