Using genetic algorithms as a parameter estimation tool for the generalized lambda distribution (gld) family: “methods of moments”

The generalized lambda distribution, λ,λ,λ,λ(GLD ) 1 432 is a four-parameter family that has been used for fitting distributions to a wide variety of data sets. Minimization through traditional calculus-based methods has been implemented with relative success, but due to computational and theoretica...

Full description

Saved in:

Bibliographic Details
Main Authors:	Moreno Bedoya, David Leonardo, Fino Puerto, Nelson Ricardo
Format:	Digital
Language:	spa
Published:	UNIVERSIDAD ANTONIO NARIÑO 2014
Subjects:	Data Fitting Generalized Lambda Distribution Minimization Method Moments Percentiles Genetic Algorithms
Online Access:	https://revistas.uan.edu.co/index.php/ingeuan/article/view/212
Tags:	Add Tag No Tags, Be the first to tag this record!

_version_	1812645009949720576
author	Moreno Bedoya, David Leonardo Fino Puerto, Nelson Ricardo
author_facet	Moreno Bedoya, David Leonardo Fino Puerto, Nelson Ricardo
author_sort	Moreno Bedoya, David Leonardo
collection	OJS
description	The generalized lambda distribution, λ,λ,λ,λ(GLD ) 1 432 is a four-parameter family that has been used for fitting distributions to a wide variety of data sets. Minimization through traditional calculus-based methods has been implemented with relative success, but due to computational and theoretical shortcomings of those methods, the moment space has been limited. This paper solve those troubles by using Genetic Algorithms (search algorithms based on the mechanics of natural selection and natural genetics) applied to the methods of moments. Examples of better solutions than the ones find out with traditional calculusbased methods are included.
format	Digital
id	revistas.uan.edu.co-article-212
institution	Revista INGE@UAN
language	spa
publishDate	2014
publisher	UNIVERSIDAD ANTONIO NARIÑO
record_format	ojs
spelling	revistas.uan.edu.co-article-2122021-02-16T16:48:16Z Using genetic algorithms as a parameter estimation tool for the generalized lambda distribution (gld) family: “methods of moments” Using genetic algorithms as a parameter estimation tool for the generalized lambda distribution (gld) family: “methods of moments” Moreno Bedoya, David Leonardo Fino Puerto, Nelson Ricardo Data Fitting Generalized Lambda Distribution Minimization Method Moments Percentiles Genetic Algorithms The generalized lambda distribution, λ,λ,λ,λ(GLD ) 1 432 is a four-parameter family that has been used for fitting distributions to a wide variety of data sets. Minimization through traditional calculus-based methods has been implemented with relative success, but due to computational and theoretical shortcomings of those methods, the moment space has been limited. This paper solve those troubles by using Genetic Algorithms (search algorithms based on the mechanics of natural selection and natural genetics) applied to the methods of moments. Examples of better solutions than the ones find out with traditional calculusbased methods are included. The generalized lambda distribution, λ,λ,λ,λ(GLD ) 1 432 is a four-parameter family that has been used for fitting distributions to a wide variety of data sets. Minimization through traditional calculus-based methods has been implemented with relative success, but due to computational and theoretical shortcomings of those methods, the moment space has been limited. This paper solve those troubles by using Genetic Algorithms (search algorithms based on the mechanics of natural selection and natural genetics) applied to the methods of moments. Examples of better solutions than the ones find out with traditional calculusbased methods are included. UNIVERSIDAD ANTONIO NARIÑO 2014-03-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.uan.edu.co/index.php/ingeuan/article/view/212 INGE@UAN - TENDENCIAS EN LA INGENIERÍA; Vol. 1 Núm. 2 (2011) 2346-1446 2145-0935 spa https://revistas.uan.edu.co/index.php/ingeuan/article/view/212/174 https://creativecommons.org/licenses/by-nc-sa/4.0
spellingShingle	Data Fitting Generalized Lambda Distribution Minimization Method Moments Percentiles Genetic Algorithms Moreno Bedoya, David Leonardo Fino Puerto, Nelson Ricardo Using genetic algorithms as a parameter estimation tool for the generalized lambda distribution (gld) family: “methods of moments”
title	Using genetic algorithms as a parameter estimation tool for the generalized lambda distribution (gld) family: “methods of moments”
title_alt	Using genetic algorithms as a parameter estimation tool for the generalized lambda distribution (gld) family: “methods of moments”
title_full	Using genetic algorithms as a parameter estimation tool for the generalized lambda distribution (gld) family: “methods of moments”
title_fullStr	Using genetic algorithms as a parameter estimation tool for the generalized lambda distribution (gld) family: “methods of moments”
title_full_unstemmed	Using genetic algorithms as a parameter estimation tool for the generalized lambda distribution (gld) family: “methods of moments”
title_short	Using genetic algorithms as a parameter estimation tool for the generalized lambda distribution (gld) family: “methods of moments”
title_sort	using genetic algorithms as a parameter estimation tool for the generalized lambda distribution gld family methods of moments
topic	Data Fitting Generalized Lambda Distribution Minimization Method Moments Percentiles Genetic Algorithms
topic_facet	Data Fitting Generalized Lambda Distribution Minimization Method Moments Percentiles Genetic Algorithms
url	https://revistas.uan.edu.co/index.php/ingeuan/article/view/212
work_keys_str_mv	AT morenobedoyadavidleonardo usinggeneticalgorithmsasaparameterestimationtoolforthegeneralizedlambdadistributiongldfamilymethodsofmoments AT finopuertonelsonricardo usinggeneticalgorithmsasaparameterestimationtoolforthegeneralizedlambdadistributiongldfamilymethodsofmoments