Interval Estimation of Bounded Variable Means via Inverse Sampling

TL;DR

This paper introduces a sequential sampling method for constructing confidence intervals of bounded variable means, stopping when the sample sum reaches a set threshold, enhancing estimation accuracy.

Contribution

It proposes a novel inverse sampling approach for interval estimation of bounded means, improving upon traditional fixed-sample methods.

Findings

Effective in providing accurate confidence intervals.

Reduces sample size compared to fixed-sample methods.

Applicable to various bounded variable scenarios.

Abstract

In this paper, we develop interval estimation methods for means of bounded random variables based on a sequential procedure such that the sampling is continued until the sample sum is no less than a prescribed threshold.