Monroy-Castillo, Blanca E.Jácome, M. A.Cao, Ricardo2023-11-132023-11-132023http://hdl.handle.net/2183/34180Cursos e Congresos, C-155[Abstract] The notion of distance correlationwas introduced to measure the dependence between two random vectors, not necessarily of equal dimensions, in a multivariate setting. In their work, Sz´ekely et al. (2007) proposed an estimator for the squared distance covariance, and they also proved that this estimator is a V-statistic. On the other hand, Sz´ekely and Rizzo (2014) introduced an unbiased version of the squared sample distance covariance, which was subsequently identified as a U-statistic in Huo and Sz´ekely (2016). In this study, a simulation is conducted to compare both distance correlation estimators: the U-estimator and the V-estimator. The analysis assesses their efficiency (mean squared error) and contrasts the computational times of both approaches across various dependence structures.engAttribution 4.0 International (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/deed.esCorrelación de distanciaVectores aleatoriosconference outputopen access