Ye, Zhi-Sheng Xie, Min Tang, Loon-Ching Chen, Nan Semiparametric Estimation of Gamma Processes for Deteriorating Products <div><p>This article investigates the semiparametric inference of the simple Gamma-process model and a random-effects variant. Maximum likelihood estimates of the parameters are obtained through the EM algorithm. The bootstrap is used to construct confidence intervals. A simulation study reveals that an estimation based on the full likelihood method is more efficient than the pseudo likelihood method. In addition, a score test is developed to examine the existence of random effects under the semiparametric scenario. A comparison study using a fatigue-crack growth dataset shows that performance of a semiparametric estimation is comparable to the parametric counterpart. This article has supplementary material online.</p></div> em;Maximum likelihood estimates;article;semiparametric;likelihood method;estimation 2015-05-07
    https://tandf.figshare.com/articles/dataset/Semiparametric_Estimation_of_Gamma_Processes_for_Deteriorating_Products/1266501
10.6084/m9.figshare.1266501.v2