威布尔分布生存函数的鲁棒估计

IF 1.6 Q1 STATISTICS & PROBABILITY
D. Karagöz, N. A. Tutkun
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引用次数: 0

摘要

本研究的目的是估计威布尔分布的鲁棒生存函数。由于威布尔分布的生存函数是基于参数的,我们考虑了Boudt et al.(2011)提出的两个鲁棒和显式威布尔参数估计器。分位数和分位数最小二乘对截尾数据都具有鲁棒性,可用来替代威布尔参数的极大似然估计。所提出的估计量应用于霍奇金病数据,该数据对鲁棒生存函数产生较小的方差。新方法的优点是它们在应用程序中是数字显式的。通过蒙特卡罗仿真比较了所提出的鲁棒估计器在考虑不同审查率的右、左和区间审查观测值存在下的行为。仿真结果表明,所提出的鲁棒估计量优于极大似然估计量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Estimations of Survival Function for Weibull Distribution
The aim of this study is to estimate the robust survival function for the Weibull distribution. Since the survival function of Weibull distribution is based on the parameters, we consider two robust and explicit Weibull parameter estimators proposed by Boudt et al. (2011). The quantile and the quantile least squares which are all robust to censored data is used as an alternative to the maximum likelihood estimation of the Weibull parameters. The proposed estimators are applied to Hodgin’s disease data which produces smaller variances for the robust survival function. The advantage of new methods is that they are numerically explicit in applications. Monte Carlo simulation is performed to compare the behaviours of the proposed robust estimators in the presence of right, left and interval censored observations considering different censoring rates. The simulation results show that the proposed robust estimators are better than the maximum likelihood estimator.
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来源期刊
Statistica
Statistica STATISTICS & PROBABILITY-
CiteScore
1.70
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0.00%
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10 weeks
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