Advances and Applications in Statistics
Volume 90, Issue 1, Pages 1 - 34
(November 2023) http://dx.doi.org/10.17654/0972361723061 |
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PREDICTING FUTURE DATA FROM GAMMA-MIXTURE AND BETA-MIXTURE DISTRIBUTIONS AND APPLICATION TO THE RECOVERY RATE OF COVID-19
O. M. Khaled, K. S. Khalil and M. H. Harpy
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Abstract: This paper addresses the problem of predicting future order statistics arising from mixture distributions. This study generalizes Barakat et al.’s [1] work that focused only on the data from a mixture of exponential distributions to wide models including the mixture-gamma and beta-mixture distributions. For these two lifetime models, we construct prediction intervals and point predictions for future observations. Two cases are considered, in the first case, we assume a fixed sample size, while in the second case, the sample size is assumed to be a positive integer-valued random variable independent of the observations. A simulation study is carried out for corroborating the finding and illustrative purposes. Finally, a practical application of the proposed method is applied to the recovery rate of COVID-19 data sets.
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Keywords and phrases: mixture distributions, predictive interval, gamma distribution, beta distribution, point predictor, COVID-19.
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