A New Hybrid Estimator for the Generalized Weibull Family Distribution

  •  Hesham Riad    
  •  Ahmed Hashish    


The method of moments (MOM) is suffered from a trouble in their corresponding estimators for the bounded distributions, which is nonfeasibility. In the sense that the supports inferred from the estimates fail to contain all observations. In this paper, we introduce a new hybrid estimator based on the MOM estimators for the generalized Weibull family distribution (GWFD). Monte Carlo simulation is performed to compare the hybrid moments estimators with the associated MOM estimators in terms of bias and root mean square error. The proposed hybrid estimator is easy to use, always feasible and it has more desirable properties than the associated MOM estimators.

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