Marshall-Olkin Extended Gumbel Type-II Distribution: Properties and Applications

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Due to the advance computer technology, the use of probability distributions has been raised up to solve the real life problems. These applications are found in reliability engineering, computer sciences, economics, psychology, survival analysis, and some others. This study offers a new probability model called Marshall-Olkin Extended Gumbel Type-II (MOEGT-II) which can model various shapes of the failure rate function. The proposed distribution is capable to model increasing, decreasing, reverse J-shaped, and upside down bathtub shapes of the failure rate function. Various statistical properties of the proposed distribution are derived such as alternate expressions for the density and distribution function, special cases of MOEGT-II distribution, quantile function, Lorenz curve, and Bonferroni curve. Estimation of the unknown parameters is carried out by the method of maximum likelihood. A simulation study is conducted using three different iterative methods with different samples of sizes n. The usefulness and potentiality of the MOEGT-II distribution have been shown using three real life data sets. The MOEGT-II distribution has been demonstrated as better fit than Exponentiated Gumbel Type-II (EGT-II), Marshall-Olkin Gumbel Type-II (MOGT-II), Gumbel Type-II (GT-II), Marshall-Olkin-Frechet (MOF), Frechet (F), Burr III, Log Logistic (LL), Beta Inverse Weibull (BIW), and Kumaraswamy Inverse Weibull (KIW) distributions.

Original languageEnglish
Article number2219570
JournalComplexity
Volume2022
DOIs
StatePublished - 2022

Fingerprint

Dive into the research topics of 'Marshall-Olkin Extended Gumbel Type-II Distribution: Properties and Applications'. Together they form a unique fingerprint.

Cite this