GLDEX: Fitting Single and Mixture of Generalised Lambda Distributions (RS and FMKL) using Various Methods

The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqplots, KS-resample tests and comparing mean, variance, skewness and kurtosis of the data with the fitted distribution.

Depends: cluster, grDevices, graphics, stats
Published: 2016-12-26
Author: Steve Su, with contributions from: Diethelm Wuertz, Martin Maechler and Rmetrics core team members for low discrepancy algorithm, Juha Karvanen for L moments codes, Robert King for gld C codes and starship codes, Benjamin Dean for corrections and input in ks.gof code and R core team for histsu function.
Maintainer: Steve Su < at>
License: GPL (≥ 3)
NeedsCompilation: yes
Materials: README
In views: Cluster, Distributions
CRAN checks: GLDEX results


Reference manual: GLDEX.pdf
Package source: GLDEX_2.0.0.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: GLDEX_2.0.0.5.tgz, r-oldrel: GLDEX_2.0.0.5.tgz
Old sources: GLDEX archive

Reverse dependencies:

Reverse depends: GLDreg
Reverse suggests: fitteR


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