Martinez-Florez, GuillermoGuillermoMartinez-FlorezGallardo, Diego I.Diego I.GallardoVenegas, OsvaldoOsvaldoVenegasBolfarine, HelenoHelenoBolfarineGomez, Hector W.Hector W.Gomez2025-12-302025-12-3020212227-7390https://hdl.handle.net/20.500.12740/23887The main object of this paper is to propose a new asymmetric model more flexible than the generalized Gaussian model. The probability density function of the new model can assume bimodal or unimodal shapes, and one of the parameters controls the skewness of the model. Three simulation studies are reported and two real data applications illustrate the flexibility of the model compared with traditional proposals in the literature.Acceso Abiertopower normal distributionbimodal asymmetric distributionmomentsmaximum likelihood estimatorsfisher information matrixhttp://dx.doi.org/10.3390/math9243183