Interval Estimation of Parameters of Log-Gamma Distribution Based on Progressively Censored Data

Abstract

Abstract A conditional method of inference is used to derive confidence intervals for the location and scale parameters as well as the quantiles and the reliability function of the log-gamma distribution when the data are progressively Type-II censored. The method is then compared to the unconditional method of constructing confidence intervals for these parameters. Finally, we illustrate all the methods of inference discussed in this paper with a numerical example.