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Application of COVID-19 Pandemic by Using Odd Lomax-G Inverse Weibull Distribution |
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PP: 47-57 |
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doi:10.18576/msl/100203
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Author(s) |
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Ehab M. Almetwally,
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Abstract |
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| The aim of this paper is to introduce a new superior distribution for modeling of mortality rate for the COVID-19 pandemic of France from 1 January to 20 February 2021. A new distribution is a combination of the inverse Weibull distribution and the odd Lomax-G family to formulate the odd Lomax-G inverse Weibull (OLIW) distribution with four parameters. A simple linear representation, hazard function, hazard rate function, rth-moment, moment generating function, and Re ́nyi entropy have been obtained of OLIW distribution. To estimate the unknown parameters of OLIW distribution, we use maximum Liklihhod, maximum product spacing, and Bayesian estimation methods. For the Bayesian approximation, the Metropolis-Hasting algorithm and square error loss function are used. To evaluate the use of estimation methods, a numerical result from the Monte Carlo simulation is obtained.
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