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

This paper proposes a two-parameter inverse Gaussian distribution IGS(μ, m) based on the coefficient of variation, where one parameter μ 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(μ, 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.