Examinando por Autor "Barranco-Chamorro, Inmaculada"

Mostrando 1 - 3 de 3
  • Miniatura
    Ítem
    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.
  • Miniatura
    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.
  • Miniatura
    Ítem
    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.