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147 results on '"Venegas, Osvaldo"'

2. Two-point distortion theorems for harmonic mappings

Author

Bravo, Víctor, Hernández, Rodrigo, and Venegas, Osvaldo

Subjects
Mathematics - Complex Variables, Primary: 30C45, 30C99, Secondary: 31C05
Abstract

We establish two-point distortion theorems for sense-preserving planar harmonic mappings $f=h+\overline{g}$ which satisfies the univalence criteria in the unit disc such that, Becker's and Nehari`s harmonic version. In addition, we find the sharp two-point distortion theorem when $h$ is a convex function, and normalized mappings such that $h(\D)$ is a $c$-linearly connected domain. To do this, we use the order of this family.

Published
2022

4. A new approach for the univalence of certain integral of harmonic mappings

Author

Arbeláez, Hugo, Bravo, Víctor, Hernández, Rodrigo, Sierra, Willy, and Venegas, Osvaldo

Subjects
Mathematics - Complex Variables, Primary: 30C45, 44A20, Secondary: 30C55
Abstract

The principal goal of this paper is to extend the classical problem of find the values of $\alpha\in \C$ for which the mappings, either $F_\alpha(z)=\int_0^z(f(\zeta)/\zeta)^\alpha d\zeta$ or $f_\alpha(z)=\int_0^z(f'(\zeta))^\alpha d\zeta$ are univalent, whenever $f$ belongs to some subclasses of univalent mappings in $\D$, but in the case of harmonic mappings, considering the \textit{shear construction} introduced by Clunie and Sheil-Small in \cite{CSS}.

Published
2019

12. Scale Mixture of Gleser Distribution with an Application to Insurance Data.

Author

Olmos, Neveka M., Gómez-Déniz, Emilio, and Venegas, Osvaldo

Subjects
BETA distribution, INSURANCE, PHYSICAL distribution of goods, FISHER information
Abstract

In this paper, the scale mixture of the Gleser (SMG) distribution is introduced. This new distribution is the product of a scale mixture between the Gleser (G) distribution and the Beta (a , 1) distribution. The SMG distribution is an alternative to distributions with two parameters and a heavy right tail. We study its representation and some basic properties, maximum likelihood inference, and Fisher's information matrix. We present an application to a real dataset in which the SMG distribution shows a better fit than two other known distributions. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Unit-bimodal Birnbaum-Saunders distribution with applications.

Author

Martínez-Flórez, Guillermo, Olmos, Neveka M., and Venegas, Osvaldo

Subjects
CENSORING (Statistics), RANDOM variables, REGRESSION analysis, PARAMETER estimation, CUMULATIVE distribution function, MAXIMUM likelihood statistics
Abstract

In this paper, we consider a transformation in a random variable which follows a bimodal Birnbaum-Saunders distribution. We propose the unit-bimodal Birnbaum-Saunders (UBBS) distribution and investigate some of its important properties, like cumulative distribution function, moments, survival function and risk function. We apply the UBBS distribution to censored data inflated at zero and one. We used the maximum likelihood approach for parameter estimation and to compare the models. Given the flexibility in UBBS distribution modes, our proposal performs best in beta regression models with zero and/or one excess. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Modified Unit-Half-Normal Distribution with Applications.

Author

Alvarez, Paulina I., Varela, Héctor, Cortés, Isaac E., Venegas, Osvaldo, and Gómez, Héctor W.

Subjects
CONTINUOUS distributions, RANDOM variables, MAXIMUM likelihood statistics, ORDER statistics, PERCENTILES
Abstract

In this article, we introduce a new continuous distribution based on the unit interval. This distribution is generated from a transformation of a random variable with half-normal distribution. We study its basic properties, percentiles, moments and order statistics. Maximum likelihood estimation is applied, and we present a simulation study to observe the behavior of the maximum likelihood estimators. We examine two applications to real proportions datasets, where the new distribution is shown to provide a better fit than other distributions defined in the unit interval. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Scale Mixture of Maxwell-Boltzmann Distribution

Author

Castillo, Jaime S., primary, Gaete, Katherine P., additional, Muñoz, Héctor A., additional, Gallardo, Diego I., additional, Bourguignon, Marcelo, additional, Venegas, Osvaldo, additional, and Gómez, Héctor W., additional

Published
2023
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27. An Exponentiated Skew-Elliptic Nonlinear Extension to the Log–Linear Birnbaum–Saunders Model with Diagnostic and Residual Analysis.

Author

Martínez-Flórez, Guillermo, Gómez, Yolanda M., and Venegas, Osvaldo

Subjects
LOG-linear models, NONLINEAR regression, MAXIMUM likelihood statistics, REGRESSION analysis, PARAMETER estimation, SAMPLING (Process)
Abstract

In this paper, we propose a nonlinear regression model with exponentiated skew-elliptical errors distributed, which can be fitted to datasets with high levels of asymmetry and kurtosis. Maximum likelihood estimation procedures in finite samples are discussed and the information matrix is deduced. We carried out a diagnosis of the influence for the nonlinear model. To analyze the sensitivity of the maximum likelihood estimators of the model's parameters to small perturbations in distribution assumptions and parameter estimation, we studied the perturbation schemes, the case weight, and the explanatory and response variables of perturbations; we also carried out a residual analysis of the deviance components. Simulation studies were performed to assess some properties of the estimators, showing the good performance of the proposed estimation procedure in finite samples. Finally, an application to a real dataset is presented. [ABSTRACT FROM AUTHOR]

Published
2023
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30. The Slashed Power Half-Normal Distribution with Applications

Author

Universidad de Sevilla. Departamento de Estadística e Investigación Operativa, Barrios, Leonardo, Gómez, Yolanda M., Venegas, Osvaldo, Barranco Chamorro, Inmaculada, Gómez, Héctor W., Universidad de Sevilla. Departamento de Estadística e Investigación Operativa, Barrios, Leonardo, Gómez, Yolanda M., Venegas, Osvaldo, Barranco Chamorro, Inmaculada, and Gómez, Héctor W.

Abstract

In this paper, an extension of the power half-normal (PHN) distribution is introduced. This new model is built on the application of slash methodology for positive random variables. The result is a distribution with greater kurtosis than the PHN; i.e., its right tail is heavier than the PHN distribution. Its probability density, survival and hazard rate function are studied, and moments, skewness and kurtosis coefficientes are obtained, along with relevant properties of interest in reliability. It is also proven that the new model can be expressed as the scale mixture of a PHN and a uniform distribution. Moreover, the new model holds the PHN distribution as a limit case when the new parameter tends to infinity. The parameters in the model are estimated by the method of moments and maximum likelihood. A simulation study is given to illustrate the good behavior of maximum likelihood estimators. Two real applications to survival and fatigue fracture data are included, in which our proposal outperforms other models.

Published
2022

35. The modified slash Lindley–Weibull distribution with applications to nutrition data.

Author

Reyes, Jimmy, Arrué, Jaime, Venegas, Osvaldo, and Gómez, Héctor W.

Subjects
MONTE Carlo method, DISTRIBUTION (Probability theory), RANDOM variables, MAXIMUM likelihood statistics, KURTOSIS, NUTRITION, PDF (Computer file format)
Abstract

This work presents an extension of the slash Lindley–Weibull distribution, of which it can be considered a modification. The new family is obtained by using the quotient of two independent random variables: a two-parameter Lindley–Weibull distribution divided by a power of the exponential distribution with parameter equal to 2. We present the pdf and cdf of the new distribution, analyzing their risk functions. Some statistical properties are studied and the moments and coefficients of asymmetry and kurtosis are shown. The parameter estimation problem is carried out by the maximum likelihood method. The method is assessed by a Monte Carlo simulation study. We use nutrition data, which are characterized by high kurtosis, to illustrate the usefulness of the proposed model. [ABSTRACT FROM AUTHOR]

Published
2022
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