Maximum Likelihood Estimation for the Parameters of the Generalized Gompertz Distribution under Progressive Type-II Right Censored Samples

Abstract

In this study, it is obtained maximum likelihood estimators (MLEs) for the unknown parameters of the Generalized Gompertz  (GG) distribution under progressive type II censored sample. The MLEs can not be obtained in closed forms. But, MLEs can be computed with Newton Raphson method. The Mean Square Error (MSE)s and biases of the ML estimators are computed using Monte Carlo simulation method.