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...

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Main Authors: Moreno Bedoya, David Leonardo, Fino Puerto, Nelson Ricardo
Format: info:eu-repo/semantics/article
Language:spa
Published: UNIVERSIDAD ANTONIO NARIÑO 2014
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Online Access:https://revistas.uan.edu.co/index.php/ingeuan/article/view/212
https://repositorio.uan.edu.co/handle/123456789/10397
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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 DSpace
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 info:eu-repo/semantics/article
id repositorio.uan.edu.co-123456789-10397
institution Repositorio Digital UAN
language spa
publishDate 2014
publisher UNIVERSIDAD ANTONIO NARIÑO
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spelling repositorio.uan.edu.co-123456789-103972024-10-14T03:48:48Z 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. 2014-03-04 2024-10-10T02:24:28Z 2024-10-10T02:24:28Z info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/version/c_970fb48d4fbd8a85 https://revistas.uan.edu.co/index.php/ingeuan/article/view/212 https://repositorio.uan.edu.co/handle/123456789/10397 spa https://revistas.uan.edu.co/index.php/ingeuan/article/view/212/174 https://creativecommons.org/licenses/by-nc-sa/4.0 http://purl.org/coar/access_right/c_abf2 application/pdf UNIVERSIDAD ANTONIO NARIÑO INGE@UAN - TENDENCIAS EN LA INGENIERÍA; Vol. 1 Núm. 2 (2011) 2346-1446 2145-0935
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_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
url https://revistas.uan.edu.co/index.php/ingeuan/article/view/212
https://repositorio.uan.edu.co/handle/123456789/10397
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