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General two-parameter distribution: Statistical properties, estimation, and application on COVID-19.
Gemeay, Ahmed M; Halim, Zeghdoudi; Abd El-Raouf, M M; Hussam, Eslam; Abdulrahman, Alanazi Talal; Mashaqbah, Nour Khaled; Alshammari, Nawaf; Makumi, Nicholas.
  • Gemeay AM; Department of Mathematics, Faculty of Science, Tanta University, Tanta, Egypt.
  • Halim Z; LaPS laboratory, Badji mokhtar University, Annaba, Algeria.
  • Abd El-Raouf MM; Basic and Applied Science Institute, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria, Egypt.
  • Hussam E; Department of Mathematics, Faculty of Science, Helwan University, Cairo, Egypt.
  • Abdulrahman AT; Department of Mathematics, College of Science, University of Ha'il, Ha'il, Saudi Arabia.
  • Mashaqbah NK; Department of educational administration, Faculty of Education, University of Ha'il, Ha'il, Saudi Arabia.
  • Alshammari N; Biology Department, College of Science, University of Ha'il, Ha'il, Saudi Arabia.
  • Makumi N; Pan African University, Institute for Basic Sciences, Technology and Innovation (PAUSTI), Nairobi, Kenya.
PLoS One ; 18(2): e0281474, 2023.
Article in English | MEDLINE | ID: covidwho-2230287
ABSTRACT
In this paper, we introduced a novel general two-parameter statistical distribution which can be presented as a mix of both exponential and gamma distributions. Some statistical properties of the general model were derived mathematically. Many estimation methods studied the estimation of the proposed model parameters. A new statistical model was presented as a particular case of the general two-parameter model, which is used to study the performance of the different estimation methods with the randomly generated data sets. Finally, the COVID-19 data set was used to show the superiority of the particular case for fitting real-world data sets over other compared well-known models.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Randomized controlled trials Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2023 Document Type: Article Affiliation country: Journal.pone.0281474

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Randomized controlled trials Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2023 Document Type: Article Affiliation country: Journal.pone.0281474