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kdevine

This package implements a vine copula based kernel density estimator. The estimator does not suffer from the curse of dimensionality and is therefore well suited for high-dimensional applications (see, Nagler and Czado, 2016). The package is built on top of the copula density estimators in kdecopula and let's you choose from all its implemented methods. The package can handle discrete and categorical data via continuous convolution.


How to install

You can install:

  • the stable release on CRAN:

    install.packages("kdevine")
  • the latest development version:

    devtools::install_github("tnagler/kdevine")

Functionality

A detailed description of of all functions and options can be found in the API documentaion. In short, the package provides the following functionality:

  • Class kdevine and its methods:

    • kdevine(): Multivariate kernel density estimation based on vine copulas. Implements the estimator of (see, Nagler and Czado, 2016).

    • dkdevine(), rkdevine(): Density and simulation functions.

  • Class kdevinecop and its methods:

    • kdevinecop(): Kernel estimator for the vine copula density (see, Nagler and Czado, 2016).

    • dkdevinecop(), rkdevinecop(): Density and simulation functions.

    • contour.kdevinecop(): Matrix of contour plots of all pair-copulas.

  • Class kde1d and its methods:

    • kde1d(): Univariate kernel density estimation for bounded and unbounded support.

    • dke1d(), pkde1d(), rkde1d(): Density, cdf, and simulation functions.

    • plot.kde1d(), lines.kde1d(): Plots the estimated density.

References

Nagler, T., Czado, C. (2016) Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas Journal of Multivariate Analysis 151, 69-89 (doi:10.1016/j.jmva.2016.07.003, preprint)

Nagler, T., Schellhase, C. and Czado, C. (2017) Nonparametric estimation of simplified vine copula models: comparison of methods arXiv:1701.00845

Nagler, T. (2017) A generic approach to nonparametric function estimation with mixed data arXiv:1704.07457

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Install

install.packages('kdevine')

Monthly Downloads

231

Version

0.4.1

License

GPL-3

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Last Published

May 19th, 2017

Functions in kdevine (0.4.1)

dkdevine

Evaluate the density of a kdevine object
dkdevinecop

Working with a kdevinecop object
wdbc

Wisconsin Diagnostic Breast Cancer (WDBC)
kde1d

Univariate kernel density estimation for bounded and unbounded support
kdevine-package

Kernel Smoothing for Bivariate Copula Densities
kdevine

Kernel density estimatior based on simplified vine copulas
kdevinecop

Kernel estimation of vine copula densities
contour.kdevinecop

Contour plots of pair copula kernel estimates
dkde1d

Working with a kde1d object
plot.kde1d

Plotting kde1d objects
rkdevine

Simulate from a kdevine object