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

Joint Authors

Yang, Fan
Ren, Hu
Hu, Zhili

Source

Mathematical Problems in Engineering

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-05-23

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Civil Engineering

Abstract EN

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.

American Psychological Association (APA)

Yang, Fan& Ren, Hu& Hu, Zhili. 2019. Maximum Likelihood Estimation for Three-Parameter Weibull Distribution Using Evolutionary Strategy. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1196455

Modern Language Association (MLA)

Yang, Fan…[et al.]. Maximum Likelihood Estimation for Three-Parameter Weibull Distribution Using Evolutionary Strategy. Mathematical Problems in Engineering No. 2019 (2019), pp.1-8.
https://search.emarefa.net/detail/BIM-1196455

American Medical Association (AMA)

Yang, Fan& Ren, Hu& Hu, Zhili. Maximum Likelihood Estimation for Three-Parameter Weibull Distribution Using Evolutionary Strategy. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1196455

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1196455