Probit Transformation for Nonparametric Kernel Estimation of the Copula Density

@article{Geenens2014ProbitTF,
  title={Probit Transformation for Nonparametric Kernel Estimation of the Copula Density},
  author={G. Geenens and Arthur Charpentier and Davy Paindaveine},
  journal={Bernoulli},
  year={2014},
  volume={23},
  pages={1848-1873}
}
  • G. Geenens, Arthur Charpentier, Davy Paindaveine
  • Published 2014
  • Mathematics
  • Bernoulli
  • Copula modelling has become ubiquitous in modern statistics. Here, the problem of nonparametricallyestimating a copula density is addressed. Arguably the most popular nonparametric density estimator,the kernel estimator is not suitable for the unit-square-supported copula densities, mainly because it isheavily a↵ected by boundary bias issues. In addition, most common copulas admit unbounded densities,and kernel methods are not consistent in that case. In this paper, a kernel-type copula density… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 86 REFERENCES
    Probit Transformation for Kernel Density Estimation on the Unit Interval
    27
    Nonparametric estimation of copula functions for dependence modelling
    130
    Asymptotic properties of the Bernstein density copula estimator for alpha-mixing data
    36
    Bernstein estimator for unbounded copula densities
    13
    Transformations to reduce boundary bias in kernel density estimation
    184
    Estimating a bivariate density when there are extra data on one or both components
    19
    Improved kernel estimation of copulas: Weak convergence and goodness-of-fit testing
    107
    Locally parametric nonparametric density estimation
    265
    Kernel Based Goodness-of-Fit Tests for Copulas with Fixed Smoothing Parameters
    73
    Kernel Based Goodness-of-Fit Test for Copulas with Fixed Smoothing Parameters
    1