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: | 1.0.4.4 |
| Depends: | cluster |
| Published: | 2012-10-24 |
| 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) |
| URL: | http://www.uwa.edu.au/people/steve.su |
| NeedsCompilation: | yes |
| In views: | Cluster, Distributions |
| CRAN checks: | GLDEX results |
| Package source: | GLDEX_1.0.4.4.tar.gz |
| MacOS X binary: | GLDEX_1.0.4.4.tgz |
| Windows binary: | GLDEX_1.0.4.4.zip |
| Reference manual: | GLDEX.pdf |