Matemática e Estatística / Mathematics and Statistics
URI permanente desta comunidade:
Navegar
Percorrer Matemática e Estatística / Mathematics and Statistics por Objetivos de Desenvolvimento Sustentável (ODS) "08:Trabalho Digno e Crescimento Económico"
A mostrar 1 - 3 de 3
Resultados por página
Opções de ordenação
- Analysis of the inequality into distributions: an alternative approach to the Gini index applied to the spending environmental in EUPublication . Seijas-Macias, Antonio; Oliveira, Amilcar; Oliveira, Teresa A.The Gini index is the most common tool to measure inequality into two distributions. Traditionally, the Gini index and the curve of Lorenz are focused on inequalities measures in the income distribution between countries or regions. But, in the last years, several authors have shown some limitations of the Gini index. In particular, it’s less sensitive to inequality at the tail of income distribution. This type of problem in the Gini index could produce two types of reactions: a new reinterpretation of the Gini index and the proposal of some alternative measures to it. In this paper, we follow the previous work using the Csiszar f-divergence to propose using the α-divergences approach to analyze the differences between the Gini index approach and these alternatives. The Gini index has been applied to the measure of resource inequalities. The AR-Gini is an area-based measure of resource inequality that estimates inequalities between neighbourhoods regarding the consumption of specific consumer goods (Druckman and Jackson, 2008). The AR-Gini could be a useful tool to monitor the distributional impacts of resource-related interventions, but this indicator presents the same overcomes as the Gini index. We can use the Gini concentration coefficient as a measure of the concentration of distribution of a random variable, especially applied to time series of data. In recent years, several studies have studied environmental spending in the European Union (EU). We focus our analysis on the distribution of this type of spending between the countries of the EU. The objective of this study is to show the differences in indexes applied to the study of the distribution of the distribution of monetary resources to environmental conservation and the extension of environmental protected areas into the countries of the European Union (EU). In our comparative study, we use the Gini index and the α-divergence measure and compare the results to get the most accurate measure of the equity of the distribution.
- Geometrical and optimizations aspects for approximating the response surface in industryPublication . Kitsos, Christos P.; Oliveira, Teresa A. ; Oliveira, Amilcar; Pardalos, Panos and Rassias, ThemistoclesThe target of this paper is to discuss an approximation when the experimentalist tries to explore the response surface of his industrial experimentation. Different methods under different designs, have been proposed for Response Surface Methods (RSM). We discuss such designs under a geometrical point of view when the optimal response surface is tried to be estimated. A number of applications in RSM are included.
- Tail-adaptive generation of random numbers from a gamma-order normal distribution using the Ziggurat algorithm with a multivariate extensionPublication . Kitsos, Christos P.; Oliveira, Amilcar; Ulrich, Eschcol Nyamsi; Leiva, Victor; Castro, CecíliaThe Ziggurat algorithm is a well-established rejection-sampling method designed for the efficient generation of pseudo-random numbers from unimodal distributions, particularly the standard normal. In this work, we extend and adapt the Ziggurat algorithm to enable the tail-adaptive generation of random numbers from the gamma-order generalized normal distribution |a flexible family characterized by a tail-shaping parameter that governs transitions between light, Gaussian, and heavy-tailed regimes. The resulting algorithm retains the computational speed of the original Ziggurat algorithm while supporting both univariate and multivariate implementations. This extension is especially relevant in simulation-intensive contexts, such as Bayesian modeling, quantitative nance, and machine learning. We provide the mathematical foundation, reproducible implementation details, and extensive benchmarking results that validate the method's efficiency and accuracy. A multivariate extension based on radial decomposition is also introduced, demonstrating the feasibility of generating random variables from symmetric multivariate distributions in practice. To illustrate the practical utility of the proposed algorithm, we present a comprehensive Monte Carlo simulation study evaluating performance across various shape and scale con gurations. Additionally, we apply the method to real-world data from biomedical signal processing, highlighting its robustness and adaptability to empirical settings where tail behavior plays a crucial role.