Examinando por Autor "Barranco Chamorro, Inmaculada"

Mostrando 1 - 5 de 5
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    Ítem
    An Extension of the Fréchet Distribution and Applications
    (MDPI, 2024) Gómez, Yolanda M.; Barranco Chamorro, Inmaculada; Castillo, Jaime S.; Gómez, Héctor W.
    This paper presents the Slash-Exponential-Fréchet distribution, which is an expanded version of the Fréchet distribution. Through its stochastic representation, probability distribution function, moments and other relevant features are obtained. Evidence supports that the updated model displays a lighter right tail than the Fréchet model and is more flexible as for skewness and kurtosis. Results on maximum likelihood estimators are given. Our proposition’s applicability is demonstrated through a simulation study and the evaluation of two real-world datasets.
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    Flexible Birnbaum-Saunders distribution
    (MDPI, 2019) Martínez Flórez, Guillermo; Barranco Chamorro, Inmaculada; Bolfarine, Heleno; Gómez, HectorW.
    In this paper, we propose a bimodal extension of the Birnbaum–Saunders model by including an extra parameter. This new model is termed flexible Birnbaum–Saunders (FBS) and includes the ordinary Birnbaum–Saunders (BS) and the skew Birnbaum–Saunders (SBS) model as special cases. Its properties are studied. Parameter estimation is considered via an iterative maximum likelihood approach. Two real applications, of interest in environmental sciences, are included, which reveal that our proposal can perform better than other competing models.
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    Ítem
    Generalized modified slash Birnbaum-Saunders distribution
    (MDPI, 2018) Reyes, Jimmy; Barranco Chamorro, Inmaculada; Gallardo, Diego I.; Gómez, Héctor W.
    In this paper, a generalization of the modified slash Birnbaum–Saunders (BS) distribution is introduced. The model is defined by using the stochastic representation of the BS distribution, where the standard normal distribution is replaced by a symmetric distribution proposed by Reyes et al. It is proved that this new distribution is able to model more kurtosis than other extensions of BS previously proposed in the literature. Closed expressions are given for the pdf (probability density functio), along with their moments, skewness and kurtosis coefficients. Inference carried out is based on modified moments method and maximum likelihood (ML). To obtain ML estimates, two approaches are considered: Newton–Raphson and EM-algorithm. Applications reveal that it has potential for doing well in real problems.
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    New Flexible Asymmetric Log-Birnbaum–Saunders Nonlinear Regression Model with Diagnostic Analysis
    (MDPI, 2024) Martínez Flórez, Guillermo; Barranco Chamorro, Inmaculada; Gómez, Héctor W.
    A nonlinear log-Birnbaum–Saunders regression model with additive errors is introduced. It is assumed that the error term follows a flexible sinh-normal distribution, and therefore it can be used to describe a variety of asymmetric, unimodal, and bimodal situations. This is a novelty since there are few papers dealing with nonlinear models with asymmetric errors and, even more, there are few able to fit a bimodal behavior. Influence diagnostics and martingale-type residuals are proposed to assess the effect of minor perturbations on the parameter estimates, check the fitted model, and detect possible outliers. A simulation study for the Michaelis–Menten model is carried out, covering a wide range of situations for the parameters. Two real applications are included, where the use of influence diagnostics and residual analysis is illustrated.
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    Ítem
    Unit-Power Half-Normal Distribution Including QuantileRegression with Applications to Medical Data
    (MDPI, 2024) Santoro, Karol I.; Gómez, Yolanda M.; Soto, Darlin; Barranco Chamorro, Inmaculada
    In this paper, we present the unit-power half-normal distribution, derived from the power half-normal distribution, for data analysis in the open unit interval. The statistical properties of the unit-power half-normal model are described in detail. Simulation studies are carried out to evaluate the performance of the parameter estimators. Additionally, we implement the quantile regression for this model, which is applied to two real healthcare data sets. Our findings suggest that the unitpower half-normal distribution provides a robust and flexible alternative for existing models for proportion data