graphics, Rcpp, randtoolbox, stats, utils

Kernel Smoothing for Bivariate Copula Densities
Provides fast implementations of kernel smoothing techniques for bivariate copula densities, in particular density estimation and resampling.
lattice, cubature, locfit, Rcpp (>= 0.11.2), VineCopula (>=
1.2)

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

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

Provides fast implementations of kernel smoothing techniques for
bivariate copula densities, in particular density estimation and resampling.

lattice, cubature, locfit, qrng, Rcpp (>= 0.11.2), VineCopula
(>= 1.6), graphics, grDevices, stats, utils

lattice, locfit, qrng, Rcpp (>= 0.11.2), graphics, grDevices,
stats, utils

lattice, locfit, qrng, Rcpp (>= 0.11.2), graphics, grDevices,
stats, utils, quadprog

c(
person("Thomas", "Nagler", , "thomas.nagler@tum.de", c("aut", "cre")),
person("Kuangyu", "Wen",, role = "ctb")
)
Thomas Nagler [aut, cre],
Kuangyu Wen [ctb]

Provides fast implementations of kernel smoothing techniques for
bivariate copula densities, in particular density estimation and resampling,
see Nagler (2018) <doi:10.18637/jss.v084.i07>.

Kernel Density Estimation with Parametric Starts and Asymmetric
Kernels
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>,
the beta kernel of Chen (1999) <doi:10.1016/S0167-9473(99)00010-9>, and the
copula kernel of Jones & Henderson (2007) <doi:10.1093/biomet/asm068>.
User-supplied kernels, parametric starts, and bandwidths are supported.