Odd Chen-G Family of Distributions

Anzagra, Lea; Sarpong, Solomon; Nasiru, Suleman

doi:10.1007/s40745-020-00248-2

Cited by 24 publications

(16 citation statements)

References 15 publications

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“…Alternatively, we define the moments of proposed distribution from the quantile function [ 32 , 33 ]. The r th raw moment of the proposed distribution is …”

Section: Statistical Propertiesmentioning

confidence: 99%

Exponentiated Odd Lomax Exponential distribution with application to COVID-19 death cases of Nepal

Dhungana

Kumar²

2022

PLoS ONE

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This study suggested a new four-parameter Exponentiated Odd Lomax Exponential (EOLE) distribution by compounding an exponentiated odd function with Lomax distribution as a generator. The proposed model is unimodal and positively skewed whereas the hazard rate function is monotonically increasing and inverted bathtubs. Some important properties of the new distribution are derived such as quintile function and median; asymptotic properties and mode; moments; mean residual life, mean path time; mean deviation; order statistics; and Bonferroni & Lorenz curve. The value of the parameters is obtained from the maximum likelihood estimation, least-square estimation, and Cramér-Von-Mises methods. Here, a simulation study and two real data sets, “the number of deaths per day due to COVID-19 of the first wave in Nepal" and ‘‘failure stresses (In Gpa) of single carbon fibers of lengths 50 mm", have been applied to validate the different theoretical findings. The finding of an order of COVID-19 deaths in 153 days in Nepal obey the proposed distribution, it has a significantly positive relationship between the predictive test positive rate and the predictive number of deaths per day. Therefore, the intended model is an alternative model for survival data and lifetime data analysis.

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“…Alternatively, we define the moments of proposed distribution from the quantile function [ 32 , 33 ]. The r th raw moment of the proposed distribution is …”

Section: Statistical Propertiesmentioning

confidence: 99%

Exponentiated Odd Lomax Exponential distribution with application to COVID-19 death cases of Nepal

Dhungana

Kumar²

2022

PLoS ONE

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“…Usually the standard distributions will be mathematically simpler, and often other members of the family can be constructed from the standard distributions by simple transformations on the underlying standard random variable. Some recent families of distributions are: Kumaraswamy odd Burr G family of distributions by Nasir et al [1], the Marshal-Olkin Odd Lindley-G family of distributions by Jamal et al [2], The Exponentiated Kumaraswamy-G family of distributions by Silva et al [3], the Topp Leone exponentiated G family of distributions by Ibrahim et al [4], The Topp Leone Kumaraswamy-G family of distributions by Ibrahim et al [5], Odd Chen-G family of distributions by Anzagra et al [6], Modi family of continuous probability distributions by Modi et al [7].…”

Section: Original Research Articlementioning

confidence: 99%

A New Extended Generalized Inverse Exponential Distribution: Properties and Applications

Sule¹

2021

AJPAS

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The quest by researchers in the area of distribution theory in proposing new models with greater flexibility has filled literature. On this note, we proposed a new distribution called the new extended generalized inverse exponential distribution with five positive parameters, which extends and generalizes the extended generalized inverse exponential distribution. We derive some mathematical properties of the proposed model including explicit expressions for the quantile function, moments, generating function, survival, hazard rate, reversed hazard rate, cumulative hazard rate function and odds functions. The method of maximum likelihood is used to estimate the parameters of the distribution. We illustrate its potentiality with applications to three real life data sets which show that the new extended generalized inverse exponential model provides greater flexibility and better fit than other competing models considered.

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“…Another extension proposed by Chaubey and Zhang [10] according to Lehman alternatives, called the extended Chen (EC) family of distributions. Other generalizations in the literature can be found in [11,12,13,14], etc.…”

Section: Introductionmentioning

confidence: 97%

Generalized Exponential Power Distribution with Application to Complete and Censored Data

El-Monsef

El-Awady

2021

AJPAS

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The exponential power distribution (EP) is a lifetime model that can exhibit increasing and bathtub hazard rate function. This paper proposed a generalization of EP distribution, named generalized exponential power (GEP) distribution. Some properties of GEP distribution will be investigated. Recurrence relations for single moments of generalized ordered statistics from GEP distribution are established and used for characterizing the GEP distribution. Estimation of the model parameters are derived using maximum likelihood method based on complete sample, type I, type II and random censored samples. A simulation study is performed in order to examine the accuracy of the maximum likelihood estimators of the model parameters. Three applications to real data, two with censored data, are provided in order to show the superiority of the proposed model to other models.

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Odd Chen-G Family of Distributions

Cited by 24 publications

References 15 publications

Exponentiated Odd Lomax Exponential distribution with application to COVID-19 death cases of Nepal

Exponentiated Odd Lomax Exponential distribution with application to COVID-19 death cases of Nepal

A New Extended Generalized Inverse Exponential Distribution: Properties and Applications

Generalized Exponential Power Distribution with Application to Complete and Censored Data

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