Estimação dos Parâmetros Angular e Linear da Equação de Regressão linear Simples pelo Método não-Paramétrico

Alícia Bolfoni Dias, Silvano Bolfoni Dias, Luciane Flores Jacobi

Abstract


When the analysis' assumptions of simple regression are not satisfied,an alternative to estimation the coefficients of the regression equation is thenonparametric method. The objective was to compare the estimates for thecoefficients of the simple linear regression model by the least squares method withthe nonparametric method. We used data of corporal mass and stature of childrenand teenagers between 11 and 14 years old from Nova Palma (RS) town, which 59were girls and 67 were boys. In the nonparametric method was considered theestimador of Theil apud Daniel (1999) for the slope coefficient (b) and the twoestimators proposed by Dietz apud Daniel (1999) for the intercept (a). Threeequations were obtained for each one of the sexes and they were compared by theAkaike Information Criteria (AIC), the Bayesian Information Criteria (BIC) and meansquared error. We concluded that the estimates we found by the two methods werevery close, with small differences among AIC, BIC and the mean squared error ofthe three equations.



DOI: https://doi.org/10.5902/2179460X9675

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