2024/02/08 by Ali Dastbaravarde, Dastbaravarde, A., Ali Dolati +1
Decision Sciences · Engineering · Mathematics · #62H05 #62H20 #Advanced Statistical Methods and Models #FOS: Mathematics #Fault Detection and Control Systems #Multi-Criteria Decision Making #Statistics Theory (math.ST)
paper · pdf · doi:10.48550/arxiv.2402.05665
openalex publication_date 2024/02/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A popular measure of association is the tail dependence coefficient which measures the strength of dependence in either the lower-left or upper-right tail of a bivariate distribution. In this paper, we develop the idea of quantile dependence, which generalizes the notion of tail dependence and could be used to detect dependence in specific regions of the domain of a joint distribution function. Properties of the proposed quantile dependence coefficient are studied and several examples illustrate our results.