Departamento de Matemáticas

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http://repositorioabierto.uantof.cl/handle/uantof/222

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Examinando Departamento de Matemáticas por Materia "EM algorithm"

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  • Miniatura
    Ítem
    A power maxwell distribution with heavy tails and applications
    (MDPI, 2020) Segovia, Francisco A; Gómez, Yolanda M.; Venegas, Osvaldo; Gómez, Héctor W.
    In this paper we introduce a distribution which is an extension of the power Maxwell distribution. This new distribution is constructed based on the quotient of two independent random variables, the distributions of which are the power Maxwell distribution and a function of the uniform distribution (0,1) respectively. Thus the result is a distribution with greater kurtosis than the power Maxwell. We study the general density of this distribution, and some properties, moments, asymmetry and kurtosis coefficients. Maximum likelihood and moments estimators are studied. We also develop the expectation–maximization algorithm to make a simulation study and present two applications to real data.
  • Miniatura
    Ítem
    An asymmetric distribution with heavy tails and its expectation-maximization (EM) algorithm implementation
    (MDPI, 2019) Olmos, Nevenka M; Venegas, Osvaldo; Gómez, Yolanda M.; Iriarte, Yuri A.
    In this paper we introduce a new distribution constructed on the basis of the quotient of two independent random variables whose distributions are the half-normal distribution and a power of the exponential distribution with parameter 2 respectively. The result is a distribution with greater kurtosis than the well known half-normal and slashed half-normal distributions. We studied the general density function of this distribution, with some of its properties, moments, and its coefficients of asymmetry and kurtosis. We developed the expectation–maximization algorithm and present a simulation study. We calculated the moment and maximum likelihood estimators and present three illustrations in real data sets to show the flexibility of the new model.