Relative Efficiency of a Quantile Method for Estimating Parameters in Censored Two-Parameter Weibull Distributions

Abstract

In simulation studies the computer time can be much reduced by using censoring. Here a simple method based on quantiles (Q method) is compared with the Maximum Likelihood (ML) method when estimating the parameters in censored two-parameter Weibull distributions. The ML estimates being obtained using the SAS procedure NLMIXED. It is demonstrated that the estimators obtained by the Q method are less efficient than the ML estimators, but this can be compensated for by increasing the sample size which nevertheless requires much less computer time than the ML method. The ML estimates can only be obtained by an iterative process and this opens the possibility for failures in the sense that reasonable estimates are presented as unreliable, or anomalous estimates are presented as reliable. Such anomalies were never obtained with the Q method.