IMAGE CHARACTERISTICS OF TWO-PARAMETER INVERSE GAUSSIAN DISTRIBUTION BASED ON COEFFICIENT OF VARIATION AND PARAMETER ESTIMATIONS OF CONSTANT STRESS ACCELERATED LIFE UNDER INVERSE POWER LAW MODEL

Ronghua Wang; Beiqing Gu; Ping Lei; Xiaoling Xu

doi:10.11948/20260009

2027 Volume 17 Issue 1

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Ronghua Wang, Beiqing Gu, Ping Lei, Xiaoling Xu. IMAGE CHARACTERISTICS OF TWO-PARAMETER INVERSE GAUSSIAN DISTRIBUTION BASED ON COEFFICIENT OF VARIATION AND PARAMETER ESTIMATIONS OF CONSTANT STRESS ACCELERATED LIFE UNDER INVERSE POWER LAW MODEL[J]. Journal of Applied Analysis & Computation, 2027, 17(1): 27-38. doi: 10.11948/20260009

Citation:

Ronghua Wang, Beiqing Gu, Ping Lei, Xiaoling Xu. IMAGE CHARACTERISTICS OF TWO-PARAMETER INVERSE GAUSSIAN DISTRIBUTION BASED ON COEFFICIENT OF VARIATION AND PARAMETER ESTIMATIONS OF CONSTANT STRESS ACCELERATED LIFE UNDER INVERSE POWER LAW MODEL[J]. Journal of Applied Analysis & Computation, 2027, 17(1): 27-38. doi: 10.11948/20260009

IMAGE CHARACTERISTICS OF TWO-PARAMETER INVERSE GAUSSIAN DISTRIBUTION BASED ON COEFFICIENT OF VARIATION AND PARAMETER ESTIMATIONS OF CONSTANT STRESS ACCELERATED LIFE UNDER INVERSE POWER LAW MODEL

1.
Mathematics and Science College, Shanghai Normal University, Shanghai 200234, China
2.
School of Statistics and Data Science, Shanghai University of International Business and Economics, Shanghai 201620, China
3.
School of International Business, Shanghai University of International Business and Economics, Shanghai 201620, China

Author Bio: Email: wrhxxl@shnu.edu.cn(R. Wang); Email: leipingmath@163.com(P. Lei); Email: xlxu@suibe.edu.cn(X. Xu)
Corresponding author: Email: gubeiqing@suibe.edu.cn(B. Gu)

Abstract

Abstract

This paper proposes a two-parameter inverse Gaussian distribution IGS$ (\mu, m) $ based on the coefficient of variation, where one parameter $ \mu $ is referred to as the scale parameter and the other $ m $ as the shape parameter. Its advantage lies in establishing a foundation for the accelerated life testing of the two-parameter inverse Gaussian distribution through a log-linear model of the scale parameter with stress. The main focus of the paper is to theoretically demonstrate the image characteristics of the density function, failure rate function, and mean residual life of the two-parameter inverse Gaussian distribution IGS$ (\mu, m) $. For constant stress accelerated life testing under the inverse power law model, point estimation of parameters is provided. The paper concludes with two simulated case studies to illustrate the application of the method.
- Two-parameter inverse Gaussian distribution /
- coefficient of variation /
- density function /
- failure rate function /
- mean residual life /
- constant stress accelerated life test /
- inverse power law model
MSC: 62N05

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References

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