Reliability analysis of bathtub-shaped distribution using empirical Bayesian and E-Bayesian estimations under progressive Type-II censoring
被引:1
作者:
Shi, Weihua
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h-index: 0
机构:
Beijing Jiaotong Univ, Sch Math & Stat, Beijing, Peoples R ChinaBeijing Jiaotong Univ, Sch Math & Stat, Beijing, Peoples R China
Shi, Weihua
[1
]
Gui, Wenhao
论文数: 0引用数: 0
h-index: 0
机构:
Beijing Jiaotong Univ, Sch Math & Stat, Beijing, Peoples R China
Beijing Jiaotong Univ, Sch Math & Stat, 3 Shangyuancun, Beijing 100044, Peoples R ChinaBeijing Jiaotong Univ, Sch Math & Stat, Beijing, Peoples R China
Gui, Wenhao
[1
,2
]
机构:
[1] Beijing Jiaotong Univ, Sch Math & Stat, Beijing, Peoples R China
[2] Beijing Jiaotong Univ, Sch Math & Stat, 3 Shangyuancun, Beijing 100044, Peoples R China
Progressive Type-II censoring scheme;
general progressive Type-II censoring scheme;
Bathtub-shaped distribution;
Empirical Bayesian estimation;
E-Bayesian estimation;
squared error loss and LINEX loss functions;
LIFETIME DISTRIBUTION;
CHEN DISTRIBUTION;
PARAMETER;
D O I:
10.1177/1748006X231157827
中图分类号:
T [工业技术];
学科分类号:
08 ;
摘要:
This paper investigates the performance of empirical Bayesian and E-Bayesian estimation of the bathtub-shaped distribution based on the progressive Type-II censored samples. These two estimations overcome the selection of hyperparameters in the Bayesian method. The empirical Bayesian analysis employs the classical approach to determine the hyperparameters. The E-Bayesian estimation uses the prior distribution of hyperparameters to derive the expectation of Bayesian estimates. The estimates of parameters are derived under the squared error loss and LINEX loss functions. The extensive simulations show the results of the empirical Bayesian estimates and the E-Bayesain estimates. Further, the empirical Bayesian estimation is also presented to analyze the parameters of bathtub-shaped distribution based on the general progressive Type-II censored samples. The two datasets from the electromechanical field and medical survival analysis are analyzed using the empirical Bayesian and E-Bayesian methods.