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kdensity: 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.

Version: 1.1.0
Imports: assertthat, univariateML, EQL
Suggests: extraDistr, SkewHyperbolic, testthat, covr, knitr, rmarkdown
Published: 2020-09-30
DOI: 10.32614/CRAN.package.kdensity
Author: Jonas Moss, Martin Tveten
Maintainer: Jonas Moss <jonas.gjertsen at gmail.com>
BugReports: https://github.com/JonasMoss/kdensity/issues
License: MIT + file LICENSE
URL: https://github.com/JonasMoss/kdensity
NeedsCompilation: no
Materials: README NEWS
CRAN checks: kdensity results

Documentation:

Reference manual: kdensity.pdf
Vignettes: Tutorial for 'kdensity'

Downloads:

Package source: kdensity_1.1.0.tar.gz
Windows binaries: r-devel: kdensity_1.1.0.zip, r-release: kdensity_1.1.0.zip, r-oldrel: kdensity_1.1.0.zip
macOS binaries: r-release (arm64): kdensity_1.1.0.tgz, r-oldrel (arm64): kdensity_1.1.0.tgz, r-release (x86_64): kdensity_1.1.0.tgz, r-oldrel (x86_64): kdensity_1.1.0.tgz
Old sources: kdensity archive

Reverse dependencies:

Reverse imports: tscopula
Reverse suggests: TreeDist

Linking:

Please use the canonical form https://CRAN.R-project.org/package=kdensity to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.