A New Inverted Topp-Leone Distribution: Applications to the COVID-19 Mortality Rate in Two Different Countries

Almetwally, Ehab M.; Alharbi, Randa; Alnagar, Dalia; Hussam, Eslam

doi:10.3390/axioms10010025

Cited by 58 publications

(31 citation statements)

References 27 publications

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“…10 Almetwally et al(71) The authors suggested a model for fitting the COVID 19 mortality rates in the UK and Canada using optimal statistical technique. They have suggested a new two-parameter lifetime distribution by combining inverted Topp-Leone (ITL) and modified Kies inverted Topp-Leone (MKITL) distributions.…”

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confidence: 99%

Statistical Modeling for the Prediction of Infectious Disease Dissemination With Special Reference to COVID-19 Spread

Yadav

Akhter

2021

Front. Public Health

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In this review, we have discussed the different statistical modeling and prediction techniques for various infectious diseases including the recent pandemic of COVID-19. The distribution fitting, time series modeling along with predictive monitoring approaches, and epidemiological modeling are illustrated. When the epidemiology data is sufficient to fit with the required sample size, the normal distribution in general or other theoretical distributions are fitted and the best-fitted distribution is chosen for the prediction of the spread of the disease. The infectious diseases develop over time and we have data on the single variable that is the number of infections that happened, therefore, time series models are fitted and the prediction is done based on the best-fitted model. Monitoring approaches may also be applied to time series models which could estimate the parameters more precisely. In epidemiological modeling, more biological parameters are incorporated in the models and the forecasting of the disease spread is carried out. We came up with, how to improve the existing modeling methods, the use of fuzzy variables, and detection of fraud in the available data. Ultimately, we have reviewed the results of recent statistical modeling efforts to predict the course of COVID-19 spread.

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confidence: 99%

Statistical Modeling for the Prediction of Infectious Disease Dissemination With Special Reference to COVID-19 Spread

Yadav

Akhter

2021

Front. Public Health

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“…These data set up of disaster mortality rate. In addition, we notice that Almetwally et al [25] analyzed this dataset to demonstrate the suitability of the new inverted Topp-Leone model. The next set of data is a 30-days COVID-19 data set from the Netherlands, and is obtained between March 31 and April 30, 2020.…”

Section: Real Data Applicationsmentioning

confidence: 81%

“…The MKIF model's potentiality for two real datasets is demonstrated in this section. MKIF

distribution is collated with other reasonable models, namely: modified Kies inverted Topp-Leone (MKITL) distribution [25] , modified Kies exponential (MKEx) [26] , and Fréchet distribution. Some goodness-of-fit measures are used to compare the fitted distributions, including the Akaike Information (AIC), Bayesian Information (BIC), CAIC (consistent Akaike information) and HQIC (Hannan-Quinn information) criterions.…”

Section: Real Data Applicationsmentioning

confidence: 99%

“…Many researchers like Sindhu et al [23] , [24] modeled the COVID-19 data using new models. This study implemented two actual data implementations and concluded from modeling results that recent model is an ideal competitor with some known and popular models like the modified Kies inverted Topp-Leone (MKITL) [25] , modified Kies exponential (MKIEx) [26] , and Fréchet (F) distribution. In future research, we attempt to address a novel implementation for MKIF distribution based on a trimmed sample (see for more information Sindhu et al [27] , [28] ).…”

Section: Introductionmentioning

confidence: 99%

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A new modified Kies Fréchet distribution: Applications of mortality rate of Covid-19

et al. 2021

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The purpose of this paper is to identify an effective statistical distribution for examining COVID-19 mortality rates in Canada and Netherlands in order to model the distribution of COVID-19. The modified Kies Frechet (MKIF) model is an advanced three parameter lifetime distribution that was developed by incorporating the Frechet and modified Kies families. In particular with respect to current distributions, the latest one has very versatile probability functions: increasing, decreasing, and inverted U shapes are observed for the hazard rate functions, indicating that the capability of adaptability of the model. A straight forward linear representation of PDF, moment generating functions, Probability weighted moments and hazard rate functions are among the enticing features of this novel distribution. We used three different estimation methodologies to estimate the pertinent parameters of MKIF model like least squares estimators (LSEs), maximum likelihood estimators (MLEs) and weighted least squares estimators (WLSEs). The efficiency of these estimators is assessed using a thorough Monte Carlo simulation analysis. We evaluated the newest model for a variety of data sets to examine how effectively it handled data modeling. The real implementation demonstrates that the proposed model outperforms competing models and can be selected as a superior model for developing a statistical model for COVID-19 data and other similar data sets.

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“…These estimation methods would be of particular interest when comparing them with other maximum likelihood estimation procedures. For more examples of classical estimation method, see the works of Almetwally [ 25 ], El-Morshedy et al [ 26 ], Almetwally et al [ 27 ], and Sabry et al [ 28 ].…”

Section: Different Estimation Methodsmentioning

confidence: 99%

Stress‐Strength Reliability for Exponentiated Inverted Weibull Distribution with Application on Breaking of Jute Fiber and Carbon Fibers

Azm

Almetwally

Alghamdi

et al. 2021

Computational Intelligence and Neuroscience

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For the first time and by using an entire sample, we discussed the estimation of the unknown parameters θ 1 , θ 2 , and β and the system of stress-strength reliability R = P Y < X for exponentiated inverted Weibull (EIW) distributions with an equivalent scale parameter supported eight methods. We will use maximum likelihood method, maximum product of spacing estimation (MPSE), minimum spacing absolute-log distance estimation (MSALDE), least square estimation (LSE), weighted least square estimation (WLSE), method of Cramér-von Mises estimation (CME), and Anderson-Darling estimation (ADE) when X and Y are two independent a scaled exponentiated inverted Weibull (EIW) distribution. Percentile bootstrap and bias-corrected percentile bootstrap confidence intervals are introduced. To pick the better method of estimation, we used the Monte Carlo simulation study for comparing the efficiency of the various estimators suggested using mean square error and interval length criterion. From cases of samples, we discovered that the results of the maximum product of spacing method are more competitive than those of the other methods. A two real‐life data sets are represented demonstrating how the applicability of the methodologies proposed in real phenomena.

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A New Inverted Topp-Leone Distribution: Applications to the COVID-19 Mortality Rate in Two Different Countries

Cited by 58 publications

References 27 publications

Statistical Modeling for the Prediction of Infectious Disease Dissemination With Special Reference to COVID-19 Spread

Statistical Modeling for the Prediction of Infectious Disease Dissemination With Special Reference to COVID-19 Spread

A new modified Kies Fréchet distribution: Applications of mortality rate of Covid-19

Stress‐Strength Reliability for Exponentiated Inverted Weibull Distribution with Application on Breaking of Jute Fiber and Carbon Fibers

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