Family of bivariate distributions on the unit square: theoretical properties and applications.

We introduce the bivariate unit-log-symmetric model based on the bivariate log-symmetric distribution (BLS) defined in Vila [25] as a flexible family of bivariate distributions over the unit square. We then study its mathematical properties such as stochastic representations, quantiles, conditional distributions, independence of the marginal distributions and marginal moments. Maximum likelihood estimation method is discussed and examined through Monte Carlo simulation.

On the Stress-Strength Reliability of Transmuted GEV Random Variables with Applications to Financial Assets Selection.

In reliability contexts, probabilities of the type R=P(X View Article and Find Full Text PDF

[Catastrophic health expenditures: analysis of the association with socioeconomic conditions in Minas Gerais, Brazil].

This study aimed to assess catastrophic health expenditures (CHE) and its association with socioeconomic conditions in 2009, 2011 and 2013 in Minas Gerais, Brazil. A cross-sectional study was carried out with data from the Household Sample Survey. The dependent variable was the CHE in each year of the survey.

Effect of education and multimorbidity on mortality among older adults: findings from the health, well-being and ageing cohort study (SABE).

Objectives: This study assessed the moderating role of education on the relationship between multimorbidity and mortality among older adults in Brazil.

Study Design: This was a cohort study.

Methods: This study used data from 1768 participants of the Health, Well-Being and Ageing Cohort Study (SABE) who were assessed between 2006 and 2015.

Bayesian inference for the log-symmetric autoregressive conditional duration model.

This paper adapts Hamiltonian Monte Carlo methods for application in log-symmetric autoregressive conditional duration models. These recent models are based on a class of log-symmetric distributions. In this class, it is possible to model both median and skewness of the duration time distribution.