完全和多重删失数据下Burr XII参数估计的计算方法
A computational method for estimating Burr XII parameters with complete and multiple censored data
摘要：
Burr XII分布在形状和尺度上的灵活性可以使许多众所周知的概率密度函数接近。由于这些能力，Burr XII分布的使用被应用于风险分析、寿命数据分析和过程能力估计。本文进一步发展了交叉熵（CE）方法，用极大似然估计（MLE）方法估计Burr XII分布在完全数据和多重截尾数据下的参数。利用CE方法对不同参数设置和样本量下的MLE进行了仿真研究。在未经审查和审查的情况下，与其他现有的方法的结果进行比较。
英文摘要：
Flexibility in shape and scale of Burr XII distribution can make close approximation of numerous well-known probability density functions. Due to these capabilities, the usages of Burr XII distribution are applied in risk analysis, lifetime data analysis and process capability estimation. In this paper the Cross-Entropy (CE) method is further developed in terms of Maximum Likelihood Estimation (MLE) to estimate the parameters of Burr XII distribution for the complete data or in the presence of multiple censoring. A simulation study is conducted to evaluate the performance of the MLE by means of CE method for different parameter settings and sample sizes. The results are compared to other existing methods in both uncensored and censored situations.
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