Abstract
Attempts have been made to define new classes of distributions that provide more flexibility for modeling data that is skewed in nature. In this work, we propose a new family of distributions namely the Marshall-Olkin Half Logistic-G (MO-HL-G) based on the generator pioneered by [Marshall and Olkin , 1997]. This new family of distributions allows for a flexible fit to real data from several fields, such as engineering, hydrology, and survival analysis. The structural properties of these distributions are studied and its model parameters are obtained through the maximum likelihood method. We finally demonstrate the effectiveness of these models via simulation experiments.
Highlights
More work has recently been done by various authors on the development of new families of distributions through the extension of other existing continuous distributions
We propose a new family of distributions namely the Marshall-Olkin Half Logistic-G (MOHL-G) based on the generator pioneered by [Marshall and Olkin, 1997]
It is in the same vein that we develop the new family of distributions called Marshall-Olkin Half Logistic-G (MO-HL-G) family of distributions
Summary
More work has recently been done by various authors on the development of new families of distributions through the extension of other existing continuous distributions. [Lepetu et al , 2017], introduced a new class of distributions called the Marshall-Olkin Log-logistic Extended Weibull (MOLLEW) family of distributions. Their work employs the Marshall-Olkin transformation to the Log-logistic Weibull distribution to obtain more new flexible models suitable for reliability data. [Afify et al , 2017] proposed a new flexible family of distributions called the Odd exponentiated half logistic-G (OEHL-G) family of distributions using the HL distribution as the generator and studied its mathematical properties. Their results utilized the flexibility of the baseline distribution in modeling various forms of data. In Section 6. we present applications of the proposed model to real data sets and give concluding remarks under Section 7
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