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Revista Colombiana de Estadística
versión impresa ISSN 0120-1751
Resumen
MARTINEZ-FLOREZ, GUILLERMO; SALINAS, HUGO S. y BOLFARINE, HELENO. Bimodal Regression Model. Rev.Colomb.Estad. [online]. 2017, vol.40, n.1, pp.65-83. ISSN 0120-1751. https://doi.org/10.15446/rce.v40n1.51738.
Regression analysis is a technique widely used in different areas of human knowledge, with distinct distributions for the error term. It is the case, however, that regression models with the error term following a bimodal distribution are not common in the literature, perhaps due to the lack of simple to deal with bimodal error distributions. In this paper, we propose a simple to deal with bimodal regression model with a symmetric-asymmetric distribution for the error term for which for some values of the shape parameter it can be bimodal. This new distribution contains the normal and skew-normal as special cases. A real data application reveals that the new model can be extremely useful in such situations.
Palabras clave : Bimodal Distribution; Generalized Gaussian Distribution; Linear Regression; Power Regression Model.