Estimation of Distance Correlation: a Simulation-based Comparative Study

• Blanca E. Monroy-Castillo ^[1] ; M. A. Jácome ^[1] ; Ricardo Cao ^[1]
  1. [1] Universidade da Coruña

     Universidade da Coruña

     A Coruña, España

     
• Localización: VI Congreso XoveTIC: impulsando el talento científico / coord. por Javier Pereira-Loureiro , Manuel Francisco González Penedo ; Manuel Lagos Rodríguez (ed. lit.), Álvaro Leitao Rodríguez (ed. lit.), Tirso Varela Rodeiro (ed. lit.), 2023
• Idioma: inglés
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• Resumen

  • 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