Odd Lomax-Kumaraswamy Distribution: Its Properties and Applications

Yakura, Bassa Shiwaye; Sule, Ahmed Askira; Dewu, Mustapha Mohammed; Manju, Kabiru Ahmed; Mohammed, Fadimatu Bawuro

doi:10.9734/jsrr/2020/v26i430247

Cited by 1 publication

(1 citation statement)

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“…Odd Lomax-exponential distribution was introduced by Ogunsanya et al [16]. Yakura et al [17] introduced the Lomax-Kumaraswamy distribution. Marzouk et al [18] obtained a generalized odd Lomax family of distributions with applications.…”

Section: Plos Onementioning

confidence: 99%

Modeling of COVID-19 vaccination rate using odd Lomax inverted Nadarajah-Haghighi distribution

Almongy

Almetwally²,

Ahmad³

et al. 2022

PLoS ONE

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Since the spread of COVID-19 pandemic in early 2020, modeling the related factors became mandatory, requiring new families of statistical distributions to be formulated. In the present paper we are interested in modeling the vaccination rate in some African countries. The recorded data in these countries show less vaccination rate, which will affect the spread of new active cases and will increase the mortality rate. A new extension of the inverted Nadarajah-Haghighi distribution is considered, which has four parameters and is obtained by combining the inverted Nadarajah-Haghighi distribution and the odd Lomax-G family. The proposed distribution is called the odd Lomax inverted Nadarajah-Haghighi (OLINH) distribution. This distribution owns many virtuous characteristics and attractive statistical properties, such as, the simple linear representation of density function, the flexibility of the hazard rate curve and the odd ratio of failure, in addition to other properties related to quantile, the rth-moment, moment generating function, Rényi entropy, and the function of ordered statistics. In this paper we address the problem of parameter estimation from frequentest and Bayesian approach, accordingly a comparison between the performance of the two estimation methods is implemented using simulation analysis and some numerical techniques. Finally different goodness of fit measures are used for modeling the COVID-19 vaccination rate, which proves the suitability of the OLINH distribution over other competitive distributions.

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Section: Plos Onementioning

confidence: 99%