Two-Point Distortion Theorems for Harmonic Mappings(2023). Bravo, V.; Hernández, R.; Venegas, O.
9 mayo, 2023 -
We establish two-point distortion theorems for sense-preserving planar harmonic mappings f= h+ g¯ in the unit disk D which satisfy harmonic versions of the univalence criteria due to Becker and Nehari. In addition, we also find two-point distortion theorems for the cases when h is a normalized convex function and, more generally, when h(D) is a c-linearly connected domain.
First-principles calculations of hematite (α-Fe2O3) by self-consistent DFT+U+V.(2023). Naveas, N., Pulido, R., Marini, C., Hernández-Montelongo, J., & Silván, M. M.
24 enero, 2023 -
The purpose of this paper is to identify the emergence of indirect trade flows prompted by the export interaction of the world’s economies. Using data on exports from the United Nations Conference on Trade and Development (UNCTAD) for the period 2016–2021, we construct an international trade network which is analyzed through the “forgotten effects theory” that identifies tuples of countries with an origin, intermediary countries, and a destination. This approach intends to spotlight something beyond the analysis of the direct trade network by the identification of second and third-order paths. The analysis using both network analyses, as well as the forgotten effect approaches, which show that the international trade network presents a hub-and-spoke behavior in contrast to most extant research finding a core-periphery structure. The structure is then comprised of three almost separated trade networks and a hub country that bridges commerce between those networks. The contribution of this article is to move the analysis forward from other works that utilize trade networks, including those of econometric nature—such as the ones based on gravity models—by incorporating indirect relationships between countries, which could provide distinctive and novel insights into the study of economic networks.
Ejemplo Proyectos / Subir con entrada y no editar con elementor(2023). Duarte, J.; Martínez-Flórez, G.; Gallardo, D.I.; Venegas, O.; Gómez, H.W.
23 enero, 2023 -
This article introduces a bimodal model based on the epsilon-skew-normal distribution. This extension generates bimodal distributions similar to those produced by the mixture of normal distributions. We study the basic properties of this new family. We apply maximum likelihood estimators, calculate the information matrix and present a simulation study to assess parameter recovery. Finally, we illustrate the results to three real data sets, suggesting this new distribution as a plausible alternative for modelling bimodal data.
Forgotten Effects Approach to the Analysis of Complex Economic Systems: Identifying Indirect Effects on Trade Networks.(2023). Chávez-Bustamante, F.;Mardones-Arias, E.; Rojas-Mora, J.; Tijmes-Ihl, J.
18 enero, 2023 -
The purpose of this paper is to identify the emergence of indirect trade flows prompted by the export interaction of the world’s economies. Using data on exports from the United Nations Conference on Trade and Development (UNCTAD) for the period 2016–2021, we construct an international trade network which is analyzed through the “forgotten effects theory” that identifies tuples of countries with an origin, intermediary countries, and a destination. This approach intends to spotlight something beyond the analysis of the direct trade network by the identification of second and third-order paths. The analysis using both network analyses, as well as the forgotten effect approaches, which show that the international trade network presents a hub-and-spoke behavior in contrast to most extant research finding a core-periphery structure. The structure is then comprised of three almost separated trade networks and a hub country that bridges commerce between those networks. The contribution of this article is to move the analysis forward from other works that utilize trade networks, including those of econometric nature—such as the ones based on gravity models—by incorporating indirect relationships between countries, which could provide distinctive and novel insights into the study of economic networks.
A bimodal extension of the epsilon-skew-normal distribution.(2023). Duarte, J.; Martínez-Flórez, G.; Gallardo, D.I.; Venegas, O.; Gómez, H.W.
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This article introduces a bimodal model based on the epsilon-skew-normal distribution. This extension generates bimodal distributions similar to those produced by the mixture of normal distributions. We study the basic properties of this new family. We apply maximum likelihood estimators, calculate the information matrix and present a simulation study to assess parameter recovery. Finally, we illustrate the results to three real data sets, suggesting this new distribution as a plausible alternative for modelling bimodal data.
Scale mixture of Maxwell-Boltzmann distribution. (2023). Castillo, J.S.; Gaete, K.P.; Muñoz, H.A.; Gallardo, D.I.; Boourguignon, M.; Venegas, O.; Gómez, H.W.
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This paper presents a new distribution, the product of the mixture between Maxwell-Boltzmann and a particular case of the generalized gamma distributions. The resulting distribution, called the Scale Mixture Maxwell-Boltzmann, presents greater kurtosis than the recently introduced slash Maxwell-Boltzmann distribution. We obtained closed-form expressions for its probability density and cumulative distribution functions. We studied some of its properties and moments, as well as its skewness and kurtosis coefficients. Parameters were estimated by the moments and maximum likelihood methods, via the Expectation-Maximization algorithm for the latter case. A simulation study was performed to illustrate the parameter recovery. The results of an application to a real data set indicate that the new model performs very well in the presence of outliers compared with other alternatives in the literature.
An Alternative to the Log-Skew-Normal Distribution: Properties, Inference, and an Application to Air Pollutant Concentrations. (2022). Arrué, J.; Arellano-Valle, R.; Venegas, O.; Bolfarine, H.; Gómez, H.W.
18 noviembre, 2022 -
In this study, we consider an alternative to the log-skew-normal distribution. It is called the modified log-skew-normal distribution and introduces greater flexibility in the skewness and kurtosis parameters. We first study several of the main probabilistic properties of the new distribution, such as the computation of its moments and the non-existence of the moment-generating function. Parameter estimation by the maximum likelihood approach is also studied. This approach presents an overestimation problem in the shape parameter, which in some cases, can even be infinite. However, as we demonstrate, this problem is solved by adapting bias reduction using Firth’s approach. We also show that the modified log-skew-normal model likewise inherits the non-singularity of the Fisher information matrix of the untransformed model, when the shape parameter is null. Finally, we apply the modified log-skew-normal model to a real example related to pollution data.
Parametric Quantile Regression Models for Fitting Double Bounded Response with Application to COVID-19 Mortality Rate Data. (2022). Gallardo, D.; Bourguignon, M.; Gómez, Y.M.; Caamaño-Carrillo, C.; Venegas, O.
27 junio, 2022 -
In this paper, we develop two fully parametric quantile regression models, based on the power Johnson SB distribution for modeling unit interval response in different quantiles. In particular, the conditional distribution is modeled by the power Johnson SB distribution. The maximum likelihood (ML) estimation method is employed to estimate the model parameters. Simulation studies are conducted to evaluate the performance of the ML estimators in finite samples. Furthermore, we discuss influence diagnostic tools and residuals. The effectiveness of our proposals is illustrated with a data set of the mortality rate of COVID-19 in different countries. The results of our models with this data set show the potential of using the new methodology. Thus, we conclude that the results are favorable to the use of proposed quantile regression models for fitting double bounded data. View Full-Text
Keywords: COVID-19; parametric quantile regression; power Johnson SB distribution; proportion
Mathematical Modeling of Recursive Drug Delivery with Diffusion, Equilibrium, and Convection Coupling.. (2022). Hernandez-Montelongo, R.; Salazar-Araya, J.; Hernández-Montelongo, J.; Gracia-Sandoval, J.P.
22 junio, 2022 -
In this work, a mathematical model to describe drug delivery from polymer coatings on implants is proposed. Release predictability is useful for development and understanding of drug release mechanisms from controlled delivery systems. The proposed model considers a unidirectional recursive diffusion process which follows Fick’s second law while considering the convective phenomena from the polymer matrix to the liquid where the drug is delivered and the polymer–liquid drug distribution equilibrium. The resulting model is solved using Laplace transformation for two scenarios: (1) a constant initial condition for a single drug delivery experiment; and (2) a recursive delivery process where the liquid medium is replaced with fresh liquid after a fixed period of time, causing a stepped delivery rate. Finally, the proposed model is validated with experimental data.
Keywords: drug delivery; mathematical model; diffusion; convection; interface equilibrium; Fourier series
A Symmetric/Asymmetric Bimodal Extension Based on the Logistic Distribution: Properties, Simulation and Applications. (2022). Cortés, I.; Venegas, O.; Gómez, H.W.
7 junio, 2022 -
In this paper, we introduce bimodal extensions, one symmetric and one asymmetric, of the logistic distribution. We define this new density and study some basic properties. We draw inferences from the moment estimator and maximum likelihood approaches. We present a simulation study to assess the behaviour of the moment and maximum likelihood estimators. We also study the singularity of the Fisher information matrix for particular cases. We offer applications in real data and compare them with a mixture of logistics distributions.
