TY - JOUR
T1 - Exponentiated transformation of Gumbel Type-II distribution for modeling COVID-19 data
AU - Sindhu, Tabassum Naz
AU - Shafiq, Anum
AU - Al-Mdallal, Qasem M.
N1 - Publisher Copyright:
© 2020 Faculty of Engineering, Alexandria University
PY - 2021/2
Y1 - 2021/2
N2 - The aim of this study is to analyze the number of deaths due to COVID-19 for Europe and China. For this purpose, we proposed a novel three parametric model named as Exponentiated transformation of Gumbel Type-II (ETGT-II) for modeling the two data sets of death cases due to COVID-19. Specific statistical attributes are derived and analyzed along with moments and associated measures, moments generating functions, uncertainty measures, complete/incomplete moments, survival function, quantile function and hazard function, etc. Additionally, model parameters are estimated by utilizing maximum likelihood method and Bayesian paradigm. To examine efficiency of the ETGT-II model a simulation analysis is performed. Finally, using the data sets of death cases of COVID-19 of Europe and China to show adaptability of suggested model. The results reveal that it may fit better than other well-known models.
AB - The aim of this study is to analyze the number of deaths due to COVID-19 for Europe and China. For this purpose, we proposed a novel three parametric model named as Exponentiated transformation of Gumbel Type-II (ETGT-II) for modeling the two data sets of death cases due to COVID-19. Specific statistical attributes are derived and analyzed along with moments and associated measures, moments generating functions, uncertainty measures, complete/incomplete moments, survival function, quantile function and hazard function, etc. Additionally, model parameters are estimated by utilizing maximum likelihood method and Bayesian paradigm. To examine efficiency of the ETGT-II model a simulation analysis is performed. Finally, using the data sets of death cases of COVID-19 of Europe and China to show adaptability of suggested model. The results reveal that it may fit better than other well-known models.
KW - COVID-19
KW - Entropies
KW - Gumbel model
KW - Reliability analysis
KW - Stochastic order
KW - Stress-strength analysis
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U2 - 10.1016/j.aej.2020.09.060
DO - 10.1016/j.aej.2020.09.060
M3 - Article
AN - SCOPUS:85094819968
SN - 1110-0168
VL - 60
SP - 671
EP - 689
JO - Alexandria Engineering Journal
JF - Alexandria Engineering Journal
IS - 1
ER -