Parameter estimation for exponential distribution under progressive type I interval censoring

In this paper, we introduce a method of parameter estimation of progressive Type I interval censored sample and progressive type II censored sample. We propose a new parameter estimation method, that is converting the data which obtained by progressive type I interval censored, those data be used to estimate of the parameter in progressive type II censored sample. We used exponential distribution with unknown scale parameter, the maximum likelihood estimator of the parameter calculates from the two methods. A simulation is conducted to compare two kinds of methods, it is found that the proposed method obtains a better estimate than progressive Type I interval censoring method in terms of mean square error.