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基于累积误差平方和最小的参数估计方法
Parameter Estimation Method Based on Minimum Cumulative Error Square Sum
【摘要】 针对经典最小二乘法与加权最小二乘法进行两参数威布尔模型参数估计时,虽满足无偏性但不满足有效性问题,提出一种基于累积误差平方和最小的参数估计方法。基于粒子群算法对完全样本、定时截尾样本以及定数截尾样本进行参数计算,以均方根误差为指标进行效果评价,并结合相关文献数据进行实证研究。研究表明,所提参数估计方法较经典最小二乘法与加权最小二乘法的均方根误差值低,能够较好地给出两参数威布尔模型的参数估计。
【Abstract】 When using classical least squares and weighted least squares to estimate the two-parameter Weibull model parameters,it satisfies the unbiasedness well but it doesn’t satisfy the validity.Aiming at this problem,a parameter estimation method based on the minimum sum of squared cumulative errors was proposed.The parameters were calculated for full samples,time-censored samples,and fixed-number censored samples.The root mean square error was used as an indicator to evaluate the effect,and an empirical study was carried out in conjunction with relevant literature data.The research shows that the RMSE value of the proposed parameter estimation method is small than that of the least squares and weighted least squares,so it can efficiently estimate the parameters of the two-parameter Weibull model.
【Key words】 Weibull model; parameter estimation; cumulative sum of squared errors; root mean square error; particle swarm optimization;
- 【文献出处】 华南理工大学学报(自然科学版) ,Journal of South China University of Technology(Natural Science Edition) , 编辑部邮箱 ,2020年11期
- 【分类号】O212.1
- 【被引频次】8
- 【下载频次】287