The Generalized Odd Inverted Exponential-G family of Distributions: Properties and Applications
In this article, we introduce a new family of distributions, called the generalized odd inverted exponential-G family. Its main feature is to use a new flexible generalization of the so-called odd transformation based on a weighting technique. We study some of its mathematical properties such that asymptotic, quantile function, linear representation, moments, reliability, entropy, order statistics and bivariate extension. Then, the inferential aspect of the corresponding statistical model is explored. The maximum likelihood estimation of the parameters is discussed and a Monte Carlo simulation study shows the good performances of the obtained estimates. The usefulness and flexibility of the new family of distributions is demonstrated through three practical data sets. It is shown that some generalized odd inverted exponential-G special models can outperform well-established models in the literature.