Speakers
Description
In this study, a novel lifetime model with two parameters has been proposed and studied for modeling more types data used in different case of studies including symmetric, asymmetric, skewed and complex data sets. The proposed model has been obtained by compounding the exponential and XLindley distributions, and it is regarded as strong competitor for widely applied symmetrical and non symmetrical models. Several characteristics and statistical properties have been investigated. However, the estimation of the model parameters of the proposed distribution for the complete sample have been provided using two estimation methods, notably maximum likelihood estimation and Bayes techniques based on several loss functions as well as an approximate tool has been used to construct the confidence intervals for the unknown parameters of the suggested model. The estimation procedures were compared using a Monte Carlo simulation experiment to demonstrate their effectiveness. In the end, the applicability and flexibility of the recommended model have been conducted using two real lifetime datasets. In our illustration, we have compared the practicality of the recommended model with several well-known competing distributions.