An Exponentiated Multivariate Extension for the Birnbaum-Saunders Log-Linear Model

Abstract

In this work, a bivariate extension of the univariate exponentiated sinh-normal distribution is proposed. The properties of the new distribution, which is called the bivariate exponentiated sinh-normal distribution, are studied in detail, and the maximum likelihood method is considered to estimate the unknown model parameters. In addition, the extension of the new distribution to the case of regression models is proposed. Monte Carlo simulation experiments are carried out to investigate the performance of the used estimation method, and two applications to real datasets are presented for illustrative purposes.

Keywords

• sinh-normal distribution
• exponentiated distribution
• maximum likelihood estimation
• two-stage estimation procedure