Abstract

This paper aims to explore the inference of quantile differences using the quantile-based empirical likelihood (QEL) method. In contrast to traditional empirical likelihood-based approaches, the proposed method yields an explicit likelihood ratio, making it user-friendly in practical applications. Additionally, as an expansion, the comparison of quantile differences between two populations is initially considered as a measure of differences. The limiting distribution of the smoothed log-empirical likelihood ratio for both cases is theoretically derived. The paper also includes simulation studies and an analysis of a dataset comprising 6033 genes.

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