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.
| Version: |
2.0.0.7 |
| Depends: |
cluster, grDevices, graphics, stats |
| Published: |
2020-02-05 |
| 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 <allegro.su at gmail.com> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
yes |
| Materials: |
README |
| In views: |
Cluster, Distributions |
| CRAN checks: |
GLDEX results |
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