A superior extension for the Lomax distribution with application to Covid-19 infections real data

Alsuhabi, Hassan; Alkhairy, Ibrahim; Almetwally, Ehab M.; Almongy, Hisham M.; Gemeay, Ahmed M.; Hussam, Eslam; Aldallal, Ramy; Sabry, M.

doi:10.1016/j.aej.2022.03.067

Cited by 28 publications

(9 citation statements)

References 34 publications

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“…2.0, 0.5, 10.4, 3.6, 0.9, 1.0, 3.4, 2.9, 8.2, 6.5, 5.7, 3.0, 4.0, 0. The SNH distribution is validated to many other competing models, including the inverse Weibull (IW) by [29], Weibull (W) by [30], Kumaraswamy exponentiated Burr XII (KEBII) by [31], Weibull-Lomax (WL) by [32], Marshall-olkin alpha power inverse Weibull (MOAPIW) [33], Kumaraswamy Weibull (KW) by [34], and extended odd Weibull Lomax (EOWL) by [35].…”

Section: Application Of Real Datamentioning

confidence: 99%

Application of Environmental Data with New Extension of Nadarajah-Haghighi Distribution

Almetwally

Meraou

2022

Computational Journal of Mathematical and Statistical Sciences

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The sin extension of the exponential (SExEx) or sin Nadarajah-Haghighi (SNH) distribution, a new extension of the exponential distribution with two parameters, is introduced and studied in this paper. For the SNH distribution, the hazard, survival functions and some sumarized data are explored. Methods for estimating the SNH distribution parameters using maximum likelihood estimation (MLE) and maximum product spacing (MPS) are explored. To compare various estimating techniques, a numerical analysis using Monte-Carlo simulation and real data analysis is carried out. Environmental data show how the new model is superior to some well-known distributions. In comparison to several well-known distributions, the SNH model can give better matches.

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Section: Application Of Real Datamentioning

confidence: 99%

Application of Environmental Data with New Extension of Nadarajah-Haghighi Distribution

Almetwally

Meraou

2022

Computational Journal of Mathematical and Statistical Sciences

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“…Two sets of real-world COVID-19 data from a variety of countries, such as Italy and Saudi Arabia, were taken into account. For more reading, see [ 19 , 32 – 42 ].…”

Section: Major Findings and Conclusionmentioning

confidence: 99%

Novel Type I Half Logistic Burr-Weibull Distribution: Application to COVID-19 Data

Alshanbari

Odhah

Almetwally

et al. 2022

Computational and Mathematical Methods in Medicine

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In this work, we presented the type I half logistic Burr-Weibull distribution, which is a unique continuous distribution. It offers several superior benefits in fitting various sorts of data. Estimates of the model parameters based on classical and nonclassical approaches are offered. Also, the Bayesian estimates of the model parameters were examined. The Bayesian estimate method employs the Monte Carlo Markov chain approach for the posterior function since the posterior function came from an uncertain distribution. The use of Monte Carlo simulation is to assess the parameters. We established the superiority of the proposed distribution by utilising real COVID-19 data from varied countries such as Saudi Arabia and Italy to highlight the relevance and flexibility of the provided technique. We proved our superiority using both real data.

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“…In this section, we introduced application to COVID-19 data for Italy, UK, and Mexico. More studies analyzed COVID-19 data [17,[23][24][25][26][27][28][29][30].…”

Section: Application To Covid-19 Datamentioning

confidence: 99%

Information Approach for Change Point Analysis of EGGAPE Distribution and Application to COVID-19 Data

Kilai

Waititu

Kibira

et al. 2022

Mathematical Problems in Engineering

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The exponentiated generalized Gull alpha power exponential distribution is an extension of the exponential distribution that can model data characterized by various shapes of the hazard function. However, change point problem has not been studied for this distribution. In this study, the change point detection of the parameters of the exponentiated generalized Gull alpha power exponential distribution is studied using the modified information criterion. In addition, the binary segmentation procedure is used to identify multiple change point locations. The assumption is that all the parameters of the EGGAPE distributions are considered changeable. Simulation study is conducted to illustrate the power of the modified information criterion in detecting change point in the parameters with different sample sizes. Three applications related to COVID-19 data are used to demonstrate the applicability of the MIC in detecting change point in real life scenario.

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A superior extension for the Lomax distribution with application to Covid-19 infections real data

Cited by 28 publications

References 34 publications

Application of Environmental Data with New Extension of Nadarajah-Haghighi Distribution

Application of Environmental Data with New Extension of Nadarajah-Haghighi Distribution

Novel Type I Half Logistic Burr-Weibull Distribution: Application to COVID-19 Data

Information Approach for Change Point Analysis of EGGAPE Distribution and Application to COVID-19 Data

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