Lomax distribution has been widely used in economics, business and actuarial sciences. Due to its importance, we consider the statistical inference of this model under joint type-II censoring scenario. In order to estimate the parameters, we derive the Newton-Raphson(NR) procedure and we observe that most of the times in the simulation NR algorithm does not converge. Consequently, we make use of the expectation-maximization (EM) algorithm. Moreover, Bayesian estimations are also provided based on squared error, linear-exponential and generalized entropy loss functions together with the importance sampling method due to the structure of posterior density function. In the sequel, we perform a Monte Carlo simulation experiment to compare the performances of the listed methods. Mean squared error values, averages of estimated values as well as coverage probabilities and average interval lengths are considered to compare the performances of different methods. The approximate confidence intervals, bootstrap-p and bootstrap-t confidence intervals are computed for EM estimations. Also, Bayesian coverage probabilities and credible intervals are obtained. Finally, we consider the Bladder Cancer data to illustrate the applicability of the methods covered in the paper.

Lomax分布已广泛用于经济学，商业和精算科学。由于其重要性，我们考虑了联合第二类审查情景下该模型的统计推断。为了估计参数，我们推导了Newton-Raphson（NR）过程，并观察到仿真NR算法中的大多数时间都不会收敛。因此，我们利用了期望最大化（EM）算法。此外，由于后密度函数的结构，还基于平方误差，线性指数和广义熵损失函数以及重要性采样方法提供了贝叶斯估计。在续篇中，我们执行了蒙特卡洛模拟实验以比较所列方法的性能。均方误差值 估计值的平均值以及覆盖率和平均间隔长度被认为可以比较不同方法的性能。计算近似置信区间，bootstrap-p和bootstrap-t置信区间以用于EM估计。同样，获得贝叶斯覆盖率概率和可信区间。最后，我们考虑膀胱癌的数据来说明本文所述方法的适用性。