Examinando por Autor "Reyes, Jimmy"

Mostrando 1 - 6 de 6
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    Ítem
    A bimodal discrete shifted poisson distribution. A case study of tourists' length of stay
    (MDPI, 2020) Gómez-Déniz, Emilio; Pérez-Rodríguez, Jorge Vicente; Reyes, Jimmy; Gómez, Héctor W.
    Although the Poisson distribution is appropriate for modelling equi-dispersed distributions, it reflects bimodality less well. In this paper, we propose a distribution which is more suitable for the latter purpose. It can be fitted to both positively and negatively skewed data and appears to represent overdispersion phenomena correctly in count data models obtained using a Poisson distribution. Furthermore, the distribution can be normalised in terms of its mean value, and therefore covariates can be included. Our empirical results are based on tourists’ length of stay in the Canary Islands (Spain), a popular holiday destination. The study analyses data supplied by the Canary Islands Tourist Expenditure Survey. Our findings show that the model presented is valid and that the fit obtained is reasonably good.
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    A Bimodal Extension of the Beta-Binomial Distributionwith Applications
    (MDPI, 2024) Reyes, Jimmy; Najera Zuloaga, Josu; Lee, Dae-Jin; Arrué, Jaime; Iriarte, Yuri A.
    In this paper, we propose an alternative distribution to model count data exhibitinguni/bimodality. It arises as a weighted version of the beta-binomial distribution, which is defined bya parametric weight function that admits up to two modes for the resulting probability mass function.Like the baseline beta-binomial distribution, the proposed distribution performs well in modelingoverdispersed binomial data. Structural properties of the new distribution are studied. Raw momentsare derived, which are used to describe the dispersion behavior relative to the mean and the skewnessbehavior. Parameter estimation is carried out using the maximum likelihood method. A simulationstudy is conducted in order to illustrate the behavior of the estimators. Finally, two applicationsillustrating the usefulness of the proposal are presented.
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    A New Multimodal Modification of the Skew Family of Distributions: Properties and Applications to Medical and Environmental Data
    (MDPI, 2024) Reyes, Jimmy; Rojas, Mario A.; Cortés, Pedro L.; Arrué, Jaime
    The skew distribution has the characteristic of appropriately modeling asymmetric unimodal data. However, in practice, there are several cases in which the data present more than one mode. In the literature, it is possible to find a large number of authors who have studied extensions based on the skew distribution to model this type of data. In this article, a new family is introduced,consisting of a multimodal modification to the family of skew distributions. Using the methodology of the weighted version of a function, we perform the product of the density function of a family of skew distributions with a polynomial of degree 4, thus obtaining a more flexible model that allows modeling data sets, whose distribution contains at most three modes. The density function, some properties, moments, skewness coefficients, and kurtosis of this new family are presented. This study focuses on the particular cases of skew-normal and Laplace distributions, although it can be applied to any other distribution. A simulation study was carried out, to study the behavior of the model parameter estimates. Illustrations with real data, referring to medicine and environmental data, show the practical performance of the proposed model in the two particular cases presented.
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    A Weighted Skew-Logistic Distribution with Applicationsto Environmental Data
    (MDPI, 2024) Cortés, Isaac; Reyes, Jimmy; Iriarte, Yuri A.
    Skewness and bimodality properties are frequently observed when analyzing environmental data such as wind speeds, precipitation levels, and ambient temperatures. As an alternative to modeling data exhibiting these properties, we propose a flexible extension of the skew-logistic distribution. The proposal corresponds to a weighted version of the skewed logistic distribution, defined by a parametric weight function that allows shapes with up to three modes for the resulting density.Parameter estimation via the maximum likelihood approach is discussed. Simulation experiments are carried out to evaluate the performance of the estimators. Applications to environmental data illustrating the utility of the proposal are presented.
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    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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    Ítem
    Modified Slash Lindley Distribution
    (Hindawi, 2017) Reyes, Jimmy; Venegas, Osvaldo; Gómez, Héctor W.