2023/07/30 by Groeneboom, Piet, Jongbloed, Geurt
#62G05 #62N01 #FOS: Mathematics #Statistics Theory (math.ST)
paper · doi:10.48550/arxiv.2307.16168
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.