Fitting the Generalized Lambda Distribution with Location and Scale-Free Shape Functionals

The generahzed lambda distribution (gld) is a family of distributions that can take on a very wide range of shapes within one distributional form. We present a fitting method for the gld using location and scale-free shape functionals to fit the shape functions before fitting the location and scale...

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Bibliographic Details
Published in:American journal of mathematical and management sciences Vol. 27; no. 3-4; pp. 441 - 460
Main Authors: King, Robert A.R., MacGillivray, H. L.
Format: Journal Article
Language:English
Published: Taylor & Francis 01-02-2007
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Summary:The generahzed lambda distribution (gld) is a family of distributions that can take on a very wide range of shapes within one distributional form. We present a fitting method for the gld using location and scale-free shape functionals to fit the shape functions before fitting the location and scale parameters. Such functions provide an alternative to the moments as a "shape-first" approach, with the advantage of being defined for parameter values where moments are infinite. We investigate the performance of the method with a simulation study and illustrate its use to choose parameter values of the gld to approximate other distributions.
ISSN:0196-6324
2325-8454
DOI:10.1080/01966324.2007.10737708