Optimal Explicit Binomial Confidence Interval with Guaranteed Coverage Probability
Xinjia Chen
TL;DR
This paper presents an optimized explicit binomial confidence interval that reduces conservativeness while ensuring the specified coverage probability, improving statistical inference accuracy.
Contribution
It introduces an optimization method for the explicit binomial confidence interval that guarantees coverage probability with less conservativeness than existing methods.
Findings
Reduced interval conservativeness
Guaranteed coverage probability
Improved statistical inference accuracy
Abstract
In this paper, we develop an approach for optimizing the explicit binomial confidence interval recently derived by Chen et al. The optimization reduces conservativeness while guaranteeing prescribed coverage probability.
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Taxonomy
TopicsMachine Learning and Algorithms · Bayesian Modeling and Causal Inference · Formal Methods in Verification