Author: Guorong Ding; Xinru Li; Yang Shen; Jiao Fan
Title: Brief Analysis of the ARIMA model on the COVID-19 in Italy Document date: 2020_4_11
ID: ilwsrir6_12
Snippet: Parameters of the ARIMA model were estimated by autocorrelation function (ACF) graph and partial autocorrelation (PACF) correlogram. We use R to statistically analyze the fitted predictions of the cumulative number of confirmed and newly diagnosed COVID-19 in Italy, and the significance level is set at =0.05 α [9] . Steps: (1) Establish the observed time series database;.....
Document: Parameters of the ARIMA model were estimated by autocorrelation function (ACF) graph and partial autocorrelation (PACF) correlogram. We use R to statistically analyze the fitted predictions of the cumulative number of confirmed and newly diagnosed COVID-19 in Italy, and the significance level is set at =0.05 α [9] . Steps: (1) Establish the observed time series database;
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