Journal of Data Science

Abstract: This paper considers the estimation of lifetime distribution based on missing-censoring data. Using the simple empirical approach rather than the maximum likelihood argument, we obtain the parametric estimations of lifetime distribution under the assumption that the failure time follows exponential or gamma distribution. We also derive the nonparametric estimation for both continuous and discrete failure distributions under the assumption that the censoring distribution is known. The loss of efficiency due to missing-censoring is shown to be generally small if the data model is specified correctly. Identifiability issue of the lifetime distribution with missing-censoring data is also addressed.