2020
DOI: 10.1007/s13337-020-00610-1
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Statistical analysis and visualization of the potential cases of pandemic coronavirus

Abstract: A local outbreak of initially unknown cause pneumonia was detected in Wuhan (Hubei, China) in December 2019 and a novel coronavirus, the severe acute respiratory syndrome coronavirus 2, was quickly found to be causing it. Since then, the epidemic has spread to all of China's mainland provinces as well as 58 other countries and territories, with more than 87,137 confirmed cases around the globe, including 79,968 from China, 7169 from other countries as of 1 March 2020, as stated by the World Health Organizatio… Show more

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Cited by 15 publications
(13 citation statements)
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“…Other time-series models. In addition, other commonly used time-series models include linear regression models such as ARIMA and GARCH [247,253], logistic growth regression [283], Cox regression [237], multivariate and polynomial regression [6,55,105], generalized linear model and visual analysis [185], support vector regression (SVR) [102,229], regression trees [49], hazard and survival functions [237], and more modern LSTM networks [119]. In addition, temporal interpolation methods such as best fit cubic, exponential decay and Lagrange interpolation, spatial interpolation methods such as inverse distance weighting, smoothing methods such as moving average, and spatio-temporal interpolation have also been applied to fit and forecast COVID-19 case time-series.…”
Section: Time-series Modelsmentioning
confidence: 99%
“…Other time-series models. In addition, other commonly used time-series models include linear regression models such as ARIMA and GARCH [247,253], logistic growth regression [283], Cox regression [237], multivariate and polynomial regression [6,55,105], generalized linear model and visual analysis [185], support vector regression (SVR) [102,229], regression trees [49], hazard and survival functions [237], and more modern LSTM networks [119]. In addition, temporal interpolation methods such as best fit cubic, exponential decay and Lagrange interpolation, spatial interpolation methods such as inverse distance weighting, smoothing methods such as moving average, and spatio-temporal interpolation have also been applied to fit and forecast COVID-19 case time-series.…”
Section: Time-series Modelsmentioning
confidence: 99%
“…So much so, that wherever the word “statistics” is used, “data science” is mentioned and vice versa (Schwab-McCoy et al , 2020). Consequently, recent research in data science has focused primarily on how to use statistical principles as the science that collects, analyzes and understands data (Muthusami and Saritha, 2020).…”
Section: Related Workmentioning
confidence: 99%
“…Some researches even help shed light on resolving the pandemic via herd immunity [ 13 ] or map out the dynamical trajectory of the viruses [ 14 , 15 ]. Among those research, there are plenty of qualitative and quantitative research methods, in particular statistical methods: regression-related models [ 16 ], Mann-Whitney U tests, Mann-Kendal tests, Spearman’s rho, etc [ 17 , 18 ]; factorial design [ 19 ]; artificial intelligence (AI) based methods [ 20 , 21 ] and some deep learning techniques in COVID-19 diagnosis [ 22 , 23 ]. Coupling with AI, an automatic reasoning for searching the hidden features of the trend of COVID-19 is also vital [ 24 ].…”
Section: Introductionmentioning
confidence: 99%