Bibliographic citations
Gavidia, D., (2021). Mixtura finita de una distribución Birnbaum-Saunders basado en la familia de mixtura en parámetros de escala de distribuciones normal asimétrica [Pontificia Universidad Católica del Perú]. http://hdl.handle.net/20.500.12404/20560
Gavidia, D., Mixtura finita de una distribución Birnbaum-Saunders basado en la familia de mixtura en parámetros de escala de distribuciones normal asimétrica []. PE: Pontificia Universidad Católica del Perú; 2021. http://hdl.handle.net/20.500.12404/20560
@mastersthesis{renati/534439,
title = "Mixtura finita de una distribución Birnbaum-Saunders basado en la familia de mixtura en parámetros de escala de distribuciones normal asimétrica",
author = "Gavidia Pucllas, Daniel Elías",
publisher = "Pontificia Universidad Católica del Perú",
year = "2021"
}
The following thesis presents the nite mixtures of Birbaums-Saunders distributions based on the scale mixture of skew-normal distributions, which are called FM-BS-SMSN. This model is an extension of Maehara (2018a) study of unimodal data based on scale mixture of skew-normal distributions which are used to model extreme percentiles in the left-tail of the distribution. The proposed model can t two or more mixture of components of skewed distributions like Skew-t, Skew-slash, and skew-contaminated normal. The proposed method to accomplish the estimation of model parameters is the expectation of conditional maximization (an extension of EM algorithm). Moreover, simulations and applications are presented to illustrate the robustness of the proposed estimation method and standar errors. Finally, the last chapter presents an aplication for real data sets.
This item is licensed under a Creative Commons License