**ABSTRACT**

Lifetime distributions describe the behavior of the length of life of individuals or components in survival or reliability analyses. They are important tools in modeling the different characteristics of lifetime data sets emanating from various fields of human endeavor. Many lifetime distributions exist in the statistical literature but are commonly characterized with having many parameters which may cause estimation related problems. To trade-off between simplicity and flexibility in modeling lifetime data sets with half logistic distribution, a new extension is proposed in this paper by using the extended odd Frechet-G family of distributions. The new distribution has only two parameters and simple mathematical form that can be interpreted in terms of odds ratio. The statistical properties of the distribution, including moments, quantile function and order statistics are studied. The unknown parameters were estimated by using two different estimation methods, namely, maximum likelihood and maximum product of spacing. Monte Carlo simulation study is undertaken to compare the finite sample performance of these parameter estimation methods based on generated samples using the quantile function of the new distribution. To demonstrate suitability in favor of the proposed distribution, three real data sets were analyzed and compared with four competitive models, two from the extended odd Frechet-G family and the remaining two having the same baseline distribution as the proposed. Empirical findings show that the new two-parameter distribution compared well to the four-parameter distributions of the same family and produced better results than the other extensions of half logistic distribution.

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