论文标题
在不同损失函数下的e-bayesian估计及其lomax分布的电子-SSE
The E-Bayesian Estimation and its E-MSE of Lomax distribution under different loss functions
论文作者
论文摘要
本文研究了基于不同损失函数的Lomax分布参数的电子乘积（贝叶斯估计的期望）。在不同的损失函数下，我们计算参数的贝叶斯估计，然后计算估计值的预期以获取电子乘积估计。为了衡量估计的误差，引入了E-MSE（预期平方平方误差）。并给出了电子乘积估计和E-MSE的公式。通过应用马尔可夫链蒙特卡洛技术，我们分析了提出的方法的性能。根据E-MSE比较结果。然后，提出了实际数据集中的样本案例以进行插图。为了测试是否可以使用Lomax分布来分析数据集，进行了Kolmogorov Smirnov测试。使用真实数据，我们可以同时获得最大似然估计，并将其与电子乘积估计进行比较。最后，我们得到了在三种不同的损失函数下的贝叶斯和电子乘估计方法之间比较的结果。
This paper studies the E-Bayesian (expectation of the Bayesian estimation) estimation of the parameter of Lomax distribution based on different loss functions. Under different loss functions, we calculate the Bayesian estimation of the parameter and then calculate the expectation of the estimated value to get the E-Bayesian estimation. To measure the estimated error, the E-MSE (expected mean squared error) is introduced. And the formulas of E-Bayesian estimation and E-MSE are given. By applying Markov Chain Monte Carlo technology, we analyze the performances of the proposed methods. Results are compared on the basis of E-MSE. Then, cases of samples in real data sets are presented for illustration. In order to test whether the Lomax distribution can be used in analyzing the datasets, Kolmogorov Smirnov tests are conducted. Using real data, we can get the maximum likelihood estimation at the same time and compare it with E-Bayesian estimation. At last, we get the results of the comparison between Bayesian and E-Bayesian estimation methods under three different loss functions.
