Estimation of Distance Correlation: a Simulation-based Comparative Study
- Blanca E. Monroy-Castillo 1
- M. A. Jácome 1
- Ricardo Cao 1
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1
Universidade da Coruña
info
- Manuel Lagos Rodríguez (ed. lit.)
- Álvaro Leitao Rodríguez (ed. lit.)
- Tirso Varela Rodeiro (ed. lit.)
- Javier Pereira Loureiro (coord.)
- 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