Credible intervals and bootstrap confidence intervals in monotone regression
Statistics Theory
2023-08-01 v1 Statistics Theory
Abstract
In the recent paper [5], a Bayesian approach for constructing confidence intervals in monotone regression problems is proposed, based on credible intervals. We view this method from a frequentist point of view, and show that it corresponds to a percentile bootstrap method of which we give two versions. It is shown that a (non-percentile) smoothed bootstrap method has better behavior and does not need correction for over- or undercoverage. The proofs use martingale methods.
Cite
@article{arxiv.2307.16168,
title = {Credible intervals and bootstrap confidence intervals in monotone regression},
author = {Piet Groeneboom and Geurt Jongbloed},
journal= {arXiv preprint arXiv:2307.16168},
year = {2023}
}
Comments
23 pagesm 9 figures