Modeling of COVID-19 Cases in Pakistan Using Lifetime Probability Distributions

Haq, Muhammad Ahsan ul; Ahmed, Mukhtar; Zafar, Javeria; Ramos, Pedro Luiz

doi:10.1007/s40745-021-00338-9

Cited by 14 publications

(5 citation statements)

References 19 publications

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“…[ 21 ] provided some statistical inferences based on the exponentiated exponential model that aided in assessing covid-19 cases in Kerala. [ 22 ] compared the performance of some lifetime models, including the Weibull model, using COVID-19 data from Pakistan. Among others.…”

Section: Introductionmentioning

confidence: 99%

A New Extension of the Topp–Leone-Family of Models with Applications to Real Data

et al. 2022

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In this article, we proposed a new extension of the Topp–Leone family of distributions. Some important properties of the model are developed, such as quantile function, stochastic ordering, model series representation, moments, stress–strength reliability parameter, Renyi entropy, order statistics, and moment of residual life. A particular member called new extended Topp–Leone exponential (NETLE) is discussed. Maximum likelihood estimation (MLE), least-square estimation (LSE), and percentile estimation (PE) are used for the model parameter estimation. Simulation studies were conducted using NETLE to assess the MLE, LSE, and PE performance by examining their bias and mean square error (MSE), and the result was satisfactory. Finally, the applications of the NETLE to two real data sets are provided to illustrate the importance of the NETLG families in practice; the data sets consist of daily new deaths due to COVID-19 in California and New Jersey, USA. The new model outperformed many other existing Topp–Leone’s and exponential related distributions based on the real data illustrations.

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Section: Introductionmentioning

confidence: 99%

A New Extension of the Topp–Leone-Family of Models with Applications to Real Data

et al. 2022

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“…Riad et al [ 26 ] introduced a new lifetime distribution named the power Bilal (PB) distribution to model COVID-19 data and investigated its statistical properties. Ahsan-ul-Haq et al [ 3 ] used different probability distributions to model COVID-19 cases in Pakistan; these are some of the recent studies based on COVID-19 data. As a result, in this study, we used COVID-19 data from Delhi, India, and China.…”

Section: Introductionmentioning

confidence: 99%

Generalization of the Lindley distribution with application to COVID-19 data

Rajitha

Akhilnath

2022

Int J Data Sci Anal

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Creating new distributions with more desired and flexible qualities for modeling lifetime data has resulted in a concentrated effort to modify or generalize existing distributions. In this paper, we propose a new distribution called the power exponentiated Lindley (PEL) distribution by generalizing the Lindley distribution using the power exponentiated family of distributions, that can fit lifetime data. Then the main statistical properties such as survival function, hazard function, reverse hazard function, moments, quantile function, stochastic ordering, MRL, order statistics, etc., of the newly proposed distribution have been derived. The parameters of the distribution are estimated using the MLE method. Then, a Monte Carlo simulation study is used to check the consistency of the parameters of the PEL distribution in terms of MSE, RMSE, and bias. Finally, we implement the PEL distribution as a statistical lifetime model for the COVID-19 case fatality ratio (in %) in China and India, and the new cases of COVID-19 reported in Delhi. Then we check whether the new distribution fits the data sets better than existing well-known distributions. Different statistical measures such as the value of the log-likelihood function, K-S statistic, AIC, BIC, HQIC, and p -value are used to assess the accuracy of the model. The suggested model seems to be superior to its base model and other well-known and related models when applied to the COVID-19 data set.

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“…Yusuf et al [15] Forecasting monthly data on patients with covid 19 disease that occurred in Pakistan. Zafar, J. et al [16] Compared several daily data models of covid 19 patients in Pakistan. The model used is a 2-parameter probability distribution, namely Weibull distribution (WD), Power function distribution (PFD), Log-Logistics Distribution (LLD), Log-Normal Distribution (LND), Inverse Weibull Distribution (IWD), Gumbel Distribution (GuD).…”

Section: Introductionmentioning

confidence: 99%

The Modelling Number of Daily Death Covid 19 Data Using Some of Two and One Parameter Distributions in Indonesia

Ramadhani¹,

Yendra²,

Marizal³

et al. 2022

IJMTT

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The outbreak of COVID-19 pandemic has caused many deaths. The number of deaths that occur randomly per day has caused various problems, including reduced population, increased land for graves, and increased fear of the situation that has arisen which indirectly impacts decreased performance which ultimately weakens a country's economy. However, it is the concern of governments and others' responsibilities to provide the correct statistics and figures to take any practicable necessary steps. Where the statistical literature supposes that a model governs every real phenomenon, once we know the model, we can evaluate the dilemma. Therefore, in this article, we compare and analyze the frequency of a number of death from COVID-19 in Indonesia using the six probability modeling. Probability modeling will be carried out using six distributions, namely Weibull, Gamma, Log Normal, Amarendra, Rani and Akash will be used in this study. The maximum likelihood method will be used to get the estimated parameter from the models used in this study. The distribution will be selected based on some methods of Good of Fit Test namely graphical (pdf plot and cumulative distribution function (CDF) plot) and numerical (Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), and Log Likelihood (Log-L)). In most cases, graphical methods give the same results but their AIC and BIC results are different. The most suitable result is selected as the distribution with the lowest AIC and BIC values. In general, the Weibull distribution has been chosen as the best model.

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Modeling of COVID-19 Cases in Pakistan Using Lifetime Probability Distributions

Cited by 14 publications

References 19 publications

A New Extension of the Topp–Leone-Family of Models with Applications to Real Data

A New Extension of the Topp–Leone-Family of Models with Applications to Real Data

Generalization of the Lindley distribution with application to COVID-19 data

The Modelling Number of Daily Death Covid 19 Data Using Some of Two and One Parameter Distributions in Indonesia

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