id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-031940-bbord079	Ye, Tingqing	Analysis and prediction of confirmed COVID-19 cases in China with uncertain time series	2020-09-16		.txt	text/plain	3906	322	66	In this section, classical time series analysis is applied to modeling the cumulative number of confirmed COVID-19 cases by local transmission in China. To model the data in Table 1 , we denote the cumulative number of confirmed COVID-19 cases in China from February 13 to March 23, 2020 by X 1 , X 2 , . Thus the disturbance term cannot be regarded as a random variable, and the classical time series analysis is not appropriate for predicting the future the cumulative number of confirmed COVID-19 cases in China. In this section, we will introduce the uncertain time series analysis, including least squares estimations, residual analysis, uncertain hypothesis test, forecast value, and confidence interval. In this section, we will introduce the uncertain time series analysis, including least squares estimations, residual analysis, uncertain hypothesis test, forecast value, and confidence interval.	./cache/cord-031940-bbord079.txt	./txt/cord-031940-bbord079.txt