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gld: Estimation and Use of the Generalised (Tukey) Lambda Distribution

The generalised lambda distribution, or Tukey lambda distribution, provides a wide variety of shapes with one functional form. This package provides random numbers, quantiles, probabilities, densities and density quantiles for four different types of the distribution, the FKML (Freimer et al 1988), RS (Ramberg and Schmeiser 1974), GPD (van Staden and Loots 2009) and FM5 - see documentation for details. It provides the density function, distribution function, and Quantile-Quantile plots. It implements a variety of estimation methods for the distribution, including diagnostic plots. Estimation methods include the starship (all 4 types), method of L-Moments for the GPD and FKML types, and a number of methods for only the FKML type. These include maximum likelihood, maximum product of spacings, Titterington's method, Moments, Trimmed L-Moments and Distributional Least Absolutes.

Version: 2.6.6
Imports: stats, graphics, e1071, lmom
Published: 2022-10-23
DOI: 10.32614/CRAN.package.gld
Author: Robert King ORCID iD [aut, cre], Benjamin Dean [aut], Sigbert Klinke [aut], Paul van Staden ORCID iD [aut]
Maintainer: Robert King <Robert.King.Newcastle at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/newystats/gld/
NeedsCompilation: yes
Materials: NEWS ChangeLog
In views: Distributions
CRAN checks: gld results

Documentation:

Reference manual: gld.pdf

Downloads:

Package source: gld_2.6.6.tar.gz
Windows binaries: r-devel: gld_2.6.6.zip, r-release: gld_2.6.6.zip, r-oldrel: gld_2.6.6.zip
macOS binaries: r-release (arm64): gld_2.6.6.tgz, r-oldrel (arm64): gld_2.6.6.tgz, r-release (x86_64): gld_2.6.6.tgz, r-oldrel (x86_64): gld_2.6.6.tgz
Old sources: gld archive

Reverse dependencies:

Reverse depends: PairedData
Reverse imports: DescTools, hmix
Reverse suggests: fitteR, glmx

Linking:

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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.