A method for non-parametric finite-sample intervals that permit p% belief assignment after observing the interval but not necessarily the full data, using only a 1D prior.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Non-parametric finite-sample credible intervals with one-dimensional priors: a middle ground between Bayesian and frequentist intervals
A method for non-parametric finite-sample intervals that permit p% belief assignment after observing the interval but not necessarily the full data, using only a 1D prior.