Title: Univariate Kernel Density Estimation
person("Thibault", "Vatter",, "thibault.vatter@gmail.com", role = c("aut"))
Description: Provides an efficient implementation of univariate local polynomial
kernel density estimators that can handle bounded and discrete data. See
Imports: cctools, graphics, Rcpp, qrng, stats, utils

Imports: graphics, Rcpp, qrng, stats, utils

Imports: graphics, Rcpp, randtoolbox, stats, utils

Title: Kernel Smoothing for Bivariate Copula Densities
Description: Provides fast implementations of kernel smoothing techniques for bivariate copula densities, in particular density estimation and resampling.
Imports: lattice, cubature, locfit, Rcpp (>= 0.11.2), VineCopula (>=

Imports: lattice, cubature, locfit, qrng, Rcpp (>= 0.11.2), VineCopula
(>= 1.5), graphics, grDevices, stats, utils

person("Thomas", "Nagler", , "thomas.nagler@tum.de", c("aut", "cre"))
Description: Provides fast implementations of kernel smoothing techniques for
bivariate copula densities, in particular density estimation and resampling.

(>= 1.6), graphics, grDevices, stats, utils

Imports: lattice, locfit, qrng, Rcpp (>= 0.11.2), graphics, grDevices,

person("Thomas", "Nagler", , "thomas.nagler@tum.de", c("aut", "cre")),

bivariate copula densities, in particular density estimation and resampling,

Title: Kernel Density Estimation with Parametric Starts and Asymmetric
Description: Handles univariate non-parametric density estimation with
parametric starts and asymmetric kernels in a simple and flexible way.
Kernel density estimation with parametric starts involves fitting a
parametric density to the data before making a correction with kernel
density estimation, see Hjort & Glad (1995) <doi:10.1214/aos/1176324627>.
Asymmetric kernels make kernel density estimation more efficient on bounded
intervals such as (0, 1) and the positive half-line. Supported asymmetric
kernels are the gamma kernel of Chen (2000) <doi:10.1023/A:1004165218295>,
copula kernel of Jones & Henderson (2007) <doi:10.1093/biomet/asm068>.
User-supplied kernels, parametric starts, and bandwidths are supported.
Suggests: extraDistr, SkewHyperbolic, testthat, covr
Imports: assertthat, EQL, knitr, rmarkdown