In this paper, a new 4-parameter exponentiated generalized inverse flexible Weibull distribution is proposed. Some of its statistical properties are studied. The aim of this paper is to estimate the model parameters via several approaches, namely, maximum likelihood, maximum product spacing and Bayesian. According to Bayesian approach, several techniques are used to get the Bayesian estimators, namely, standard error function, Linex loss function and entropy loss function. The estimation herein is based on complete and censored samples. Markov Chain Monte Carlo simulation is used to discuss the behavior of the estimators for each approach. Finally, two real data sets are analyzed to obtain the flexibility of the proposed model.

本文提出了一种新的四参数指数广义逆柔性魏布尔分布。研究了其某些统计特性。本文的目的是通过几种方法来估计模型参数，即最大似然，最大乘积间隔和贝叶斯方法。根据贝叶斯方法，使用几种技术来获得贝叶斯估计量，即标准误差函数，Linex损失函数和熵损失函数。本文中的估计是基于完整且经过审查的样本。马尔可夫链蒙特卡罗模拟用于讨论每种方法的估计量的行为。最后，分析了两个实际数据集以获得所提出模型的灵活性。