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...
Saved in:
Main Authors: | , |
---|---|
Format: | info:eu-repo/semantics/article |
Language: | spa |
Published: |
UNIVERSIDAD ANTONIO NARIÑO
2014
|
Subjects: | |
Online Access: | https://revistas.uan.edu.co/index.php/ingeuan/article/view/212 https://repositorio.uan.edu.co/handle/123456789/10397 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
_version_ | 1813306066101862400 |
---|---|
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 |
record_format | dspace |
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 |
work_keys_str_mv | AT morenobedoyadavidleonardo usinggeneticalgorithmsasaparameterestimationtoolforthegeneralizedlambdadistributiongldfamilymethodsofmoments AT finopuertonelsonricardo usinggeneticalgorithmsasaparameterestimationtoolforthegeneralizedlambdadistributiongldfamilymethodsofmoments |