2020/02/02 by Freeh N. Alenezi, Alenezi, Freeh, Chris P. Tsokos +1
Computer Science · Engineering · Mathematics · #Software Reliability and Analysis Research #Reliability and Maintenance Optimization #Statistical Distribution Estimation and Applications
paper · pdf · doi:10.48550/arxiv.2002.00351
The Power Law Process, also known as Non-Homogeneous Poisson Process, has\nbeen used in various aspects, one of which is the software reliability\nassessment. Specifically, by using its intensity function to compute the rate\nof change of a software reliability as time-varying function. Justification of\nBayesian analysis applicability to the Power Law Process was shown using real\ndata. The probability distribution that best characterizes the behavior of the\nkey parameter of the intensity function was first identified, then the\nlikelihood-based Bayesian reliability estimate of the Power Law Process under\nthe Higgins-Tsokos loss function was obtained. As a result of a simulation\nstudy and using real data, the Bayesian estimate shows an outstanding\nperformance compared to the maximum likelihood estimate using different sample\nsizes. In addition, a sensitivity analysis was performed, resulting in the\nBayesian estimate being sensitive to the prior selection; whether parametric or\nnon-parametric.\n