Marshall Olkin Alpha Power Extended Weibull Distribution: Different Methods of Estimation based on Type I and Type II Censoring
Ehab M. Almetwally
Abstract
In this paper, we insert and study a novel five-parameter extended Weibull distribution denominated as the Marshall–Olkin alpha power extended Weibull (MOAPEW) distribution. This distribution's statistical properties are discussed. Maximum likelihood estimations (MLE), maximum product spacing (MPS), and Bayesian estimation for the MOAPEW distribution parameters are obtained using Type I and Type II censored samples. A numerical analysis using Monte-Carlo simulation and real data sets are realized to compare various estimation methods. The supremacy of this novel model upon some famous distributions is explicated using different real datasets as it appears the MOAPEW model achieves a good fit for these applications.
Topics & Concepts
Weibull distributionCensoring (clinical trials)MathematicsExponentiated Weibull distributionStatisticsMonte Carlo methodType (biology)Bayesian probabilityMaximum likelihoodApplied mathematicsAlgorithmBiologyEcologyStatistical Distribution Estimation and ApplicationsProbabilistic and Robust Engineering DesignStatistical Methods and Bayesian Inference