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Estimation method of mixture distribution and modeling of COVID-19 pandemic
AIMS Mathematics ; 7(6):9926-9956, 2022.
Article in English | Scopus | ID: covidwho-1780115
ABSTRACT
The mathematical characteristics of the mixture of Lindley model with 2-component (2-CMLM) are discussed. In this paper, we investigate both the practical and theoretical aspects of the 2-CMLM. We investigate several statistical features of the mixed model like probability generating function, cumulants, characteristic function, factorial moment generating function, mean time to failure, Mills Ratio, mean residual life. The density, hazard rate functions, mean, coefficient of variation, skewness, and kurtosis are all shown graphically. Furthermore, we use appropriate approaches such as maximum likelihood, least square and weighted least square methods to estimate the pertinent parameters of the mixture model. We use a simulation study to assess the performance of suggested methods. Eventually, modelling COVID-19 patient data demonstrates the effectiveness and utility of the 2-CMLM. The proposed model outperformed the two component mixture of exponential model as well as two component mixture of Weibull model in practical applications, indicating that it is a good candidate distribution for modelling COVID-19 and other related data sets. © 2022 the Author(s), licensee AIMS Press.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: AIMS Mathematics Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: AIMS Mathematics Year: 2022 Document Type: Article