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  • 标题:The Discrete Type-II Half-Logistic Exponential Distribution with Applications to COVID-19 Data
  • 本地全文:下载
  • 作者:Muhammad Ahsan ul Haq ; Ayesha Babar ; Sharqa Hashmi
  • 期刊名称:Pakistan Journal of Statistics and Operation Research
  • 印刷版ISSN:2220-5810
  • 出版年度:2021
  • 卷号:17
  • 期号:4
  • 页码:921-932
  • DOI:10.18187/pjsor.v17i4.3772
  • 语种:English
  • 出版社:College of Statistical and Actuarial Sciences
  • 摘要:We propose a new two-parameter discrete model, called discrete Type-II half-logistics exponential (DTIIHLE) distribution using the survival discretization approach. The DTIIHLE distribution can be utilized to model COVID-19 data. The model parameters are estimated using the maximum likelihood method. A simulation study is conducted to evaluate the performance of the maximum likelihood estimators. The usefulness of the proposed distribution is evaluated using two real-life COVID-19 data sets. The DTIIHLE distribution provides a superior fit to COVID-19 data as compared with competitive discrete models including the discrete-Pareto, discrete Burr-XII, discrete log-logistic, discrete-Lindley, discrete-Rayleigh, discrete inverse-Rayleigh, and natural discrete-Lindley.
  • 关键词:Discretization;type II half logistics exponential;maximum likelihood estimation;Simulation study;COVID-19
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