A note on the equivalence between the conditional uncorrelation and the independence of random variables

被引:0
|
作者
Jaworski, Piotr [1 ]
Jelito, Damian [2 ]
Pitera, Marcin [2 ]
机构
[1] Univ Warsaw, Inst Math, Warsaw, Poland
[2] Jagiellonian Univ, Inst Math, Krakow, Poland
来源
ELECTRONIC JOURNAL OF STATISTICS | 2024年 / 18卷 / 01期
关键词
Correlation; Pearson's correlation; Linear dependence; Zero conditional correlation; Zero conditional covariance; Independence; Linear independence; Local correlation; ZERO CORRELATION; DEPENDENCE;
D O I
10.1214/24-EJS2212
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
It is well known that while the independence of random variables implies zero correlation, the opposite is not true. Namely, uncorrelated random variables are not necessarily independent. In this note we show that the implication could be reversed if we consider the localised version of the correlation coefficient. More specifically, we show that if random variables are conditionally (locally) uncorrelated for any quantile conditioning sets, then they are independent. For simplicity, we focus on the absolutely continuous case. Also, we illustrate potential usefulness of the stated result using multiple examples.
引用
收藏
页码:653 / 673
页数:21
相关论文
共 50 条
  • [21] On the equivalence between conditional and random-effects likelihoods in exponential families
    De Bin, Riccardo
    STATISTICS & PROBABILITY LETTERS, 2016, 110 : 34 - 38
  • [22] Bayesian test of independence and conditional independence of two ordinal variables
    Zahra Saberi
    Mojtab Ganjali
    Journal of Statistical Theory and Applications, 2015, 14 (2): : 156 - 168
  • [23] Conditional acceptability of random variables
    Tasos C Christofides
    István Fazekas
    Milto Hadjikyriakou
    Journal of Inequalities and Applications, 2016
  • [24] Conditional acceptability of random variables
    Christofides, Tasos C.
    Fazekas, Istvan
    Hadjikyriakou, Milto
    JOURNAL OF INEQUALITIES AND APPLICATIONS, 2016,
  • [25] Bayesian test of independence and conditional independence of two ordinal variables
    Saberi, Zahra
    Ganjali, Mojtab
    JOURNAL OF STATISTICAL THEORY AND APPLICATIONS, 2015, 14 (02): : 156 - 168
  • [26] ON THE CONDITIONAL-INDEPENDENCE OF RANDOM EVENTS
    DOHLER, R
    THEORY OF PROBABILITY AND ITS APPLICATIONS, 1980, 25 (03) : 628 - 634
  • [27] On nonparametric conditional independence tests for continuous variables
    Li Chun
    Fan Xiaodan
    WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS, 2020, 12 (03):
  • [28] A NOTE ON THE ASYMPTOTIC INDEPENDENCE OF THE SUM AND MAXIMUM OF STRONGLY MIXING STATIONARY RANDOM-VARIABLES
    HSING, TL
    ANNALS OF PROBABILITY, 1995, 23 (02): : 938 - 947
  • [29] A note on the relationship between conditional and unconditional independence and its extensions for Markov kernels
    Nogales, A. G.
    Perez, P.
    STATISTICA NEERLANDICA, 2019, 73 (03) : 320 - 332
  • [30] Increasing Effect Sizes of Pairwise Conditional Independence Tests between Random Vectors
    Hochsprung, Tom
    Wahl, Jonas
    Gerhardus, Andreas
    Ninad, Urmi
    Runge, Jakob
    UNCERTAINTY IN ARTIFICIAL INTELLIGENCE, 2023, 216 : 879 - 889