Abstract
In this paper, we propose a new lifetime distribution called transmuted record type Lindley (TRTL). Some mathematical properties of the TRTL distribution are discussed namely, density shapes, moments, variance, the coefficient of skewness, coefficient of kurtosis, and moment generating function. We use the maximum likelihood method for point and interval estimation. The asymptotic confidence intervals based on maximum likelihood estimators (MLEs) are derived. A extensive Monte Carlo simulation study is performed to evaluate the performances of the MLEs with respect to mean squared error (MSE) criterion. Finally, three COVID-19 patient data examples are considered to illustrate the usefulness of the introduced model in modelling real-life data. According to the results of real-world data examples, we observe the best-fitted model is the TRTL among the competitor models.
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Data Availability
Data for this work were obtained from the web (accessed from https://data.gov.il/dataset/covid-19).
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CT contributed to introduction, transmuted record type method (TRTM), transmuted record type Lindley (TRTL) distribution, maximum likelihood estimation, simulation study, real data applications, and conclusion sections.
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Tanış, C. A new Lindley distribution: applications to COVID-19 patients data. Soft Comput 28, 2863–2874 (2024). https://doi.org/10.1007/s00500-023-09339-7
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DOI: https://doi.org/10.1007/s00500-023-09339-7