Published

2001-01-01

COMPARACIÓN DE TRES MÉTODOS DE REGRESIÓN LINEAL USANDO PROCEDIMIENTOS DE SIMULACIÓN

Keywords:

Modelo lineal, análisis de regresión, simulación (es)
Linear model, regression analysis, simulation (en)

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Authors

  • Juan Torres C. Universidad Nacional de Colombia
Cuando desea ajustarse un modelo lineal a un conjunto de datos, el método de regresión usualmente más empleado es el de mínimos cuadrados. Este método es óptimo si la distribución de los residuos es gaussiana. Existen casos en donde el supuesto de normalidad en los residuales no se cumple y se hace necesario el uso de métodos alternativos de regresión, como la regresión vía mínimas desviaciones absolutas (LAD) o la regresión no paramétrica basada en rangos, los cuales no requieren de supuestos distribucionales sobre los residuos y permiten obtener una mejor estimación de los parámetros del modelo de regresión.
When it's necessary to fit a lineal model to a data set, least squares regression method is usually used. This method is optimum if the residuals distribution is normal. When the assumption of residuals normality doesn't comply it's necessary to use alternative regression methods, as Least absolute deviations (LAD) or Non parametric regression based on ranks, which don't need the assumption about the residuals distribution and allow a better estimation of regression model parameters.

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Copyright (c) 2001 Revista Colombiana de Estadística

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