Marshall Olkin Alpha Power Extended Weibull Distribution: Different Methods of Estimation based on Type I and Type II Censoring

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.

Keywords

• Marshall–Olkin Alpha Power
• Maximum product spacing
• Bayesian estimation
• Type I censored
• Type II censored

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