Power of goodness of fit tests for the two-parameter weibull distribution with estimated parameters

Abstract

The power of several EDF goodness-of-fit statistics was evaluated for the two-parameter Weibull distribution following estimation by maximum likelihood estimators (MLE_s), good linear unbiased estimators (GLUE_s), and modified GLUEs (MGLUE_s). Relative power of Kolmogorov-Smirnov and Cramer-von Mises-type statistics was a function of level of Type I1 censoring, sample size, and method of parameter estimation. In generalW ² and A ² displayed more power than D U ², and VPower was a function of method of estimation, but no one method was superior in all situations.

Keywords:

• Cramer-von Mises
• Anderson-Darling
• Kolmogorov-Smirnov
• Watson statistic
• Ex-treme-value distribution