Abstract
A new generalized distribution is developed, namely, Topp-Leone Marshall-Olkin-G distribution. The new distribution is a linear combination of the exponentiated-G family of distributions. We considered three sub-families of the new proposed family of distribution. The distribution can handle heavy-tailed data and various forms of the hazard rate functions. A simulation study was conducted to evaluate consistency of the model parameters. Three applications are provided to demonstrate the usefulness of the new model in comparison with competing non-nested models.
Highlights
There is an increase in the demand for generalized distributions, which can handle various levels of skewness and kurtosis
These generalized models has wider applications in areas of reliability and engineering. These generalized models have wider applications in hydrology, medicine, economics, finance and insurance. In response to this demand, many generators are proposed in literature and these include beta-G by Eugene, Lee, and Famoye (2002), Marshall-Olkin-G (MO-G) by Marshall and Olkin (1997), Kumaraswamy-G (Kw-G) by Cordeiro and de Castro (2011), gamma-G by Zografos and Balakrishinan (2009), Weibull-G (W-G) by Bourguignon, Silva, and Cordeiro (2014), T-X family by Alzaatreh and Ghosh (2013), beta odd Lindley-G (BOL-G) by Chipepa, Oluyede, Makubate, and Fagbamigbe (2019), Kumaraswamy odd Lindley-G by Chipepa, Oluyede, and Makubate (2019), Topp-Leone odd log-logistic-G (TLOLL-G) by Brito, Cordeiro, Yousof, Alizadeh, and Silva (2017), to mention a few
We present the first five moments of the TL-MO-LLo distribution, and the standard deviation (SD or σ), coefficient of variation (CV), coefficient of skewness (CS) and coefficient of kurtosis (CK) for selected parameters values
Summary
There is an increase in the demand for generalized distributions, which can handle various levels of skewness and kurtosis. There is an increased need for generalized distributions that can fit data that exhibit various shapes for the hazard rate functions. These generalized models has wider applications in areas of reliability and engineering. These generalized models have wider applications in hydrology, medicine, economics, finance and insurance In response to this demand, many generators are proposed in literature and these include beta-G by Eugene, Lee, and Famoye (2002), Marshall-Olkin-G (MO-G) by Marshall and Olkin (1997), Kumaraswamy-G (Kw-G) by Cordeiro and de Castro (2011), gamma-G by Zografos and Balakrishinan (2009), Weibull-G (W-G) by Bourguignon, Silva, and Cordeiro (2014), T-X family by Alzaatreh and Ghosh (2013), beta odd Lindley-G (BOL-G) by Chipepa, Oluyede, Makubate, and Fagbamigbe (2019), Kumaraswamy odd Lindley-G by Chipepa, Oluyede, and Makubate (2019), Topp-Leone odd log-logistic-G (TLOLL-G) by Brito, Cordeiro, Yousof, Alizadeh, and Silva (2017), to mention a few.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Statistics and Probability
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
