Estimation of Distance Correlation: a Simulation-based Comparative Study

  1. Blanca E. Monroy-Castillo 1
  2. M. A. Jácome 1
  3. Ricardo Cao 1
  1. 1 Universidade da Coruña
    info

    Universidade da Coruña

    La Coruña, España

    ROR https://ror.org/01qckj285

Libro:
VI Congreso XoveTIC: impulsando el talento científico
  1. Manuel Lagos Rodríguez (ed. lit.)
  2. Álvaro Leitao Rodríguez (ed. lit.)
  3. Tirso Varela Rodeiro (ed. lit.)
  4. Javier Pereira Loureiro (coord.)
  5. Manuel Francisco González Penedo (coord.)

Editorial: Servizo de Publicacións ; Universidade da Coruña

Año de publicación: 2023

Congreso: XoveTIC (6. 2023. A Coruña)

Tipo: Aportación congreso

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