Multistage Estimation of Bounded-Variable Means

In this paper, we develop a multistage approach for estimating the mean of a bounded variable. We first focus on the multistage estimation of a binomial parameter and then generalize the estimation methods to the case of general bounded random variables. A fundamental connection between a binomial parameter and the mean of a bounded variable is established. Our multistage estimation methods rigorously guarantee prescribed levels of precision and confidence.

💡 Research Summary

The paper introduces a multistage sampling framework for estimating the mean of a bounded random variable with rigorously guaranteed precision and confidence. The authors begin by focusing on the classic problem of estimating a binomial proportion p, establishing a direct equivalence between p and the mean μ of a variable X that is confined to the interval