Exact Confidence Bounds in Discrete Models -- Algorithmic Aspects of Sterne's Method

TL;DR

This paper reviews and provides an explicit algorithm for Sterne's method to compute exact confidence bounds in discrete models like binomial and Poisson, enhancing statistical inference accuracy.

Contribution

It introduces an explicit algorithm for Sterne's method, enabling efficient computation of exact confidence bounds in various discrete models.

Findings

Algorithm successfully computes confidence bounds in examples

Method applies to binomial, Poisson, and odds ratio models

Enhances precision of statistical inference in discrete settings

Abstract

In this manuscript we review two methods to construct exact confidence bounds for an unknown real parameter in a general class of discrete statistical models. These models include the binomial family, the Poisson family as well as distributions connected to odds ratios in two-by-two tables. In particular, we discuss Sterne's (1954) method in our general framework and present an explicit algorithm for the computation of the resulting confidence bounds. The methods are illustrated with various examples.