Parameters of a distribution are generally estimated by using the classical methods such as maximum likelihood (ML) and least squares (LS) estimation. However, these classical methods are very sensitive to outliers. This study, therefore, proposes the application of the optimal B-robust (OBR) estimation method, which is resistant to outliers, to estimate the parameters of power Lindley (PL) distribution. We also provide a simulation study and a real data example to compare the performance of the OBR estimators with the performances of the ML, LS, and the regression M estimators.

中文翻译：

---

功率 Lindley 分布参数的最优 B 鲁棒估计量

分布参数的估计通常使用经典方法，例如最大似然 (ML) 和最小二乘 (LS) 估计。然而，这些经典方法对异常值非常敏感。因此，本研究提出应用抗异常值的最优 B 鲁棒 (OBR) 估计方法来估计功率 Lindley (PL) 分布的参数。我们还提供了一个模拟研究和一个真实数据示例来比较 OBR 估计器的性能与 ML、LS 和回归 M 估计器的性能。