Ahsan-Ul-Haq Muhammad, Ahmed Mukhtar, Zafar Javeria, Ramos Pedro Luiz
College of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan.
School of Statistics, Minhaj University Lahore, Lahore, Pakistan.
Ann Data Sci. 2022;9(1):141-152. doi: 10.1007/s40745-021-00338-9. Epub 2021 May 4.
The Coronavirus Disease (COVID-19) is a respiratory disease that caused a large number of deaths all over the world since its outbreak. The World Health Organization (WHO) has declared the outbreak a global pandemic. The understanding of the random process related to the behavior infection of COVID-19 is an important health and economic problem. In the proposed study, we analyze the frequency of daily confirmed cases of COVID-19 using different two-parameter lifetime probability distributions. We consider the data from the period of March 11, 2020, to July 25, 2020, of Pakistan. We consider nine lifetime probability distributions for the analysis purpose and the selection of best fit was carried out using log-likelihood, AIC, BIC, RMSE, and R goodness-of-fit measures. Results indicate that Weibull distribution provides generally the best-fit probability distribution.
冠状病毒病（COVID-19）是一种自爆发以来在全球导致大量死亡的呼吸道疾病。世界卫生组织（WHO）已宣布此次疫情为全球大流行。理解与COVID-19感染行为相关的随机过程是一个重要的健康和经济问题。在本拟议研究中，我们使用不同的双参数寿命概率分布来分析COVID-19每日确诊病例的频率。我们考虑了巴基斯坦从2020年3月11日至2020年7月25日期间的数据。为进行分析，我们考虑了九种寿命概率分布，并使用对数似然、AIC、BIC、RMSE和R拟合优度度量来选择最佳拟合。结果表明，威布尔分布通常提供最佳拟合概率分布。
