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Título : 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”
metadata.dc.creator: Moreno Bedoya, David Leonardo
Fino Puerto, Nelson Ricardo
Palabras clave : Data Fitting;Generalized Lambda Distribution;Minimization Method;Moments;Percentiles;Genetic Algorithms
Descripción : 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.
URI : http://repositorio.uan.edu.co/handle/123456789/3892
Otros identificadores : http://revistas.uan.edu.co/index.php/ingeuan/article/view/212
Editorial : UNIVERSIDAD ANTONIO NARIÑO
Aparece en las colecciones: INGE@UAN

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