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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| Formato: | Digital |
| Lenguaje: | spa |
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UNIVERSIDAD ANTONIO NARIÑO
2014
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| Acceso en línea: | https://revistas.uan.edu.co/index.php/ingeuan/article/view/212 |
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| _version_ | 1812645009949720576 |
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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 | 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 |
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