Nonparametric Testing of Conditional Independence by Means of the Partial Copula

@article{Bergsma2010NonparametricTO,
  title={Nonparametric Testing of Conditional Independence by Means of the Partial Copula},
  author={Wicher Bergsma},
  journal={Econometrics: Econometric \& Statistical Methods - General eJournal},
  year={2010}
}
  • Wicher Bergsma
  • Published 2010
  • Mathematics
  • Econometrics: Econometric & Statistical Methods - General eJournal
We propose a new method to test conditional independence of two real random variables $Y$ and $Z$ conditionally on an arbitrary third random variable $X$. The partial copula is introduced, defined as the joint distribution of $U=F_{Y|X}(Y|X)$ and $V=F_{Z|X}(Z|X)$. We call this transformation of $(Y,Z)$ into $(U,V)$ the partial copula transform. It is easy to show that if $Y$ and $Z$ are continuous for any given value of $X$, then $Y\ind Z|X$ implies $U\ind V$. Conditional independence can then… Expand
Conditional independence testing via weighted partial copulas
On the weak convergence of the empirical conditional copula under a simplifying assumption
Test for conditional independence with application to conditional screening
Conditional independence test by generalized Kendall’s tau with generalized odds ratio
Testing Conditional Independence Via Empirical Likelihood
...
1
2
3
...

References

SHOWING 1-10 OF 37 REFERENCES
Testing conditional independence using maximal nonlinear conditional correlation
A Consistent Characteristic-Function-Based Test for Conditional Independence
Testing conditional independence for continuous random variables
A NONPARAMETRIC HELLINGER METRIC TEST FOR CONDITIONAL INDEPENDENCE
Confidence Intervals for Partial Rank Correlations
A Class of Statistics with Asymptotically Normal Distribution
...
1
2
3
4
...