Maximum Likelihood Estimation for Three-Parameter Weibull Distribution Using Evolutionary Strategy

被引:21
|
作者
Yang, Fan [1 ,2 ]
Ren, Hu [3 ]
Hu, Zhili [1 ,2 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, State Key Lab Mech & Control Mech Struct, Nanjing 210016, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Coll Aerosp Engn, Nanjing 210016, Peoples R China
[3] Wuxi Hengding Supercomp Ctr Ltd, Wuxi, Jiangsu, Peoples R China
关键词
PARTICLE SWARM OPTIMIZATION; PARAMETERS;
D O I
10.1155/2019/6281781
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The maximum likelihood estimation is a widely used approach to the parameter estimation. However, the conventional algorithm makes the estimation procedure of three-parameter Weibull distribution difficult. Therefore, this paper proposes an evolutionary strategy to explore the good solutions based on the maximum likelihood method. The maximizing process of likelihood function is converted to an optimization problem. The evolutionary algorithm is employed to obtain the optimal parameters for the likelihood function. Examples are presented to demonstrate the proposed method. The results show that the proposed method is suitable for the parameter estimation of the three-parameter Weibull distribution.
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页数:8
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